diff --git a/arm_compute/core/CL/CLHelpers.h b/arm_compute/core/CL/CLHelpers.h
index ee6397a..77c17c7 100644
--- a/arm_compute/core/CL/CLHelpers.h
+++ b/arm_compute/core/CL/CLHelpers.h
@@ -206,7 +206,7 @@
  *
  * @return An opencl kernel
  */
-cl::Kernel create_kernel(CLCompileContext &ctx, const std::string &kernel_name, const std::set<std::string> &build_opts);
+cl::Kernel create_kernel(CLCompileContext &ctx, const std::string &kernel_name, const std::set<std::string> &build_opts = std::set<std::string>());
 
 /** Creates a suitable LWS hint object for parallel implementations. Sets the number of WG based on the input size.
  *  If input width is smaller than 128 we can use fewer threads than 8.
diff --git a/arm_compute/core/CL/kernels/CLAbsoluteDifferenceKernel.h b/arm_compute/core/CL/kernels/CLAbsoluteDifferenceKernel.h
index 24993e2..1889672 100644
--- a/arm_compute/core/CL/kernels/CLAbsoluteDifferenceKernel.h
+++ b/arm_compute/core/CL/kernels/CLAbsoluteDifferenceKernel.h
@@ -1,5 +1,5 @@
 /*
- * Copyright (c) 2016-2019 ARM Limited.
+ * Copyright (c) 2016-2020 ARM Limited.
  *
  * SPDX-License-Identifier: MIT
  *
@@ -58,6 +58,14 @@
      * @param[out] output Destination tensor. Data types supported: U8/S16.
      */
     void configure(const ICLTensor *input1, const ICLTensor *input2, ICLTensor *output);
+    /** Set the inputs and output images.
+     *
+     * @param[in]  compile_context The compile context to be used.
+     * @param[in]  input1          Source tensor. Data types supported: U8/S16.
+     * @param[in]  input2          Source tensor. Data types supported: U8/S16.
+     * @param[out] output          Destination tensor. Data types supported: U8/S16.
+     */
+    void configure(CLCompileContext &compile_context, const ICLTensor *input1, const ICLTensor *input2, ICLTensor *output);
 
     // Inherited methods overridden:
     void run(const Window &window, cl::CommandQueue &queue) override;
diff --git a/arm_compute/core/CL/kernels/CLAccumulateKernel.h b/arm_compute/core/CL/kernels/CLAccumulateKernel.h
index 84f3f2c..d7cb09f 100644
--- a/arm_compute/core/CL/kernels/CLAccumulateKernel.h
+++ b/arm_compute/core/CL/kernels/CLAccumulateKernel.h
@@ -1,5 +1,5 @@
 /*
- * Copyright (c) 2016-2019 ARM Limited.
+ * Copyright (c) 2016-2020 ARM Limited.
  *
  * SPDX-License-Identifier: MIT
  *
@@ -46,6 +46,13 @@
      * @param[out] accum Destination tensor. Data types supported: S16.
      */
     void configure(const ICLTensor *input, ICLTensor *accum);
+    /** Set the input and accumulation tensors.
+     *
+     * @param[in]  compile_context The compile context to be used.
+     * @param[in]  input           Source tensor. Data types supported: U8.
+     * @param[out] accum           Destination tensor. Data types supported: S16.
+     */
+    void configure(CLCompileContext &compile_context, const ICLTensor *input, ICLTensor *accum);
 };
 
 /** Interface for the accumulate weighted kernel.
@@ -67,6 +74,14 @@
      * @param[in,out] accum Accumulated tensor. Data types supported: U8.
      */
     void configure(const ICLTensor *input, float alpha, ICLTensor *accum);
+    /** Set the input and accumulation images, and the scale value.
+     *
+     * @param[in]     compile_context The compile context to be used.
+     * @param[in]     input           Source tensor. Data types supported: U8.
+     * @param[in]     alpha           Scalar value in the range [0, 1.0]. Data types supported: F32.
+     * @param[in,out] accum           Accumulated tensor. Data types supported: U8.
+     */
+    void configure(CLCompileContext &compile_context, const ICLTensor *input, float alpha, ICLTensor *accum);
 };
 
 /** Interface for the accumulate squared kernel.
@@ -86,6 +101,14 @@
      * @param[in,out] accum Accumulated tensor. Data types supported: S16.
      */
     void configure(const ICLTensor *input, uint32_t shift, ICLTensor *accum);
+    /** Set the input and accumulation tensors and the shift value.
+     *
+     * @param[in]     compile_context The compile context to be used.
+     * @param[in]     input           Source tensor. Data types supported: U8.
+     * @param[in]     shift           Shift value in the range of [0, 15]. Data types supported: U32.
+     * @param[in,out] accum           Accumulated tensor. Data types supported: S16.
+     */
+    void configure(CLCompileContext &compile_context, const ICLTensor *input, uint32_t shift, ICLTensor *accum);
 };
 } // namespace arm_compute
 #endif /*ARM_COMPUTE_CLACCUMULATEKERNEL_H */
diff --git a/arm_compute/core/CL/kernels/CLActivationLayerKernel.h b/arm_compute/core/CL/kernels/CLActivationLayerKernel.h
index 5b65a54..d25480c 100644
--- a/arm_compute/core/CL/kernels/CLActivationLayerKernel.h
+++ b/arm_compute/core/CL/kernels/CLActivationLayerKernel.h
@@ -29,13 +29,12 @@
 namespace arm_compute
 {
 class ICLTensor;
-class CLCoreRuntimeContext;
 /** Interface for the activation layer kernel. */
 class CLActivationLayerKernel : public ICLKernel
 {
 public:
     /** Default constructor */
-    CLActivationLayerKernel(CLCoreRuntimeContext *ctx = nullptr);
+    CLActivationLayerKernel();
     /** Prevent instances of this class from being copied (As this class contains pointers) */
     CLActivationLayerKernel(const CLActivationLayerKernel &) = delete;
     /** Prevent instances of this class from being copied (As this class contains pointers) */
@@ -56,6 +55,17 @@
      * @param[in]      act_info Activation layer information.
      */
     void configure(ICLTensor *input, ICLTensor *output, ActivationLayerInfo act_info);
+    /** Set the input and output tensor.
+     *
+     * @note If the output tensor is a nullptr, the activation function will be performed in-place
+     *
+     * @param[in]      compile_context The compile context to be used.
+     * @param[in, out] input           Source tensor. In case of @p output tensor = nullptr, this tensor will store the result
+     *                                 of the activation function. Data types supported: QASYMM8/QASYMM8_SIGNED/QSYMM16/F16/F32.
+     * @param[out]     output          Destination tensor. Data type supported: same as @p input
+     * @param[in]      act_info        Activation layer information.
+     */
+    void configure(CLCompileContext &compile_context, ICLTensor *input, ICLTensor *output, ActivationLayerInfo act_info);
     /** Static function to check if given info will lead to a valid configuration of @ref CLActivationLayerKernel
      *
      * @param[in] input    Source tensor info. In case of @p output tensor info = nullptr, this tensor will store the result
@@ -74,7 +84,6 @@
     ICLTensor            *_input;
     ICLTensor            *_output;
     bool                  _run_in_place;
-    CLCoreRuntimeContext *_ctx;
 };
 } // namespace arm_compute
 #endif /*ARM_COMPUTE_CLACTIVATIONLAYERKERNEL_H */
diff --git a/arm_compute/core/CL/kernels/CLArgMinMaxLayerKernel.h b/arm_compute/core/CL/kernels/CLArgMinMaxLayerKernel.h
index 7f4cfe3..831cee5 100644
--- a/arm_compute/core/CL/kernels/CLArgMinMaxLayerKernel.h
+++ b/arm_compute/core/CL/kernels/CLArgMinMaxLayerKernel.h
@@ -1,5 +1,5 @@
 /*
- * Copyright (c) 2019 ARM Limited.
+ * Copyright (c) 2019-2020 ARM Limited.
  *
  * SPDX-License-Identifier: MIT
  *
@@ -65,6 +65,18 @@
      * @param[in]  op          Reduction operation to perform. Only ArgMin and ArgMax are supported.
      */
     void configure(const ICLTensor *input, const ICLTensor *prev_output, ICLTensor *output, unsigned int axis, ReductionOperation op);
+    /** Set the input and output tensors.
+     *
+     * @param[in]  compile_context The compile context to be used.
+     * @param[in]  input           Source tensor. Data types supported: S32/F16/F32.
+     * @param[in]  prev_output     Destination tensor of the previous iterations of @ref CLArgMinMaxLayerKernel. Data types supported: U32/S32
+     *                             Has to be nullptr for the first iteration
+     * @param[out] output          Destination tensor. Data types supported: U32/S32
+     *                             Output will have the same number of dimensions as input.
+     * @param[in]  axis            Axis along which to reduce. Supported reduction axis : 0,1,2,3
+     * @param[in]  op              Reduction operation to perform. Only ArgMin and ArgMax are supported.
+     */
+    void configure(CLCompileContext &compile_context, const ICLTensor *input, const ICLTensor *prev_output, ICLTensor *output, unsigned int axis, ReductionOperation op);
 
     /** Static function to check if given info will lead to a valid configuration of @ref CLArgMinMaxLayerKernel.
      *
diff --git a/arm_compute/core/CL/kernels/CLBatchConcatenateLayerKernel.h b/arm_compute/core/CL/kernels/CLBatchConcatenateLayerKernel.h
index 3711617..0676430 100644
--- a/arm_compute/core/CL/kernels/CLBatchConcatenateLayerKernel.h
+++ b/arm_compute/core/CL/kernels/CLBatchConcatenateLayerKernel.h
@@ -61,6 +61,18 @@
      *
      */
     void configure(const ICLTensor *input, unsigned int batch_offset, ICLTensor *output);
+    /** Initialise the kernel's inputs and output
+     *
+     * @param[in]     compile_context The compile context to be used.
+     * @param[in]     input           Input tensor. Data types supported: All.
+     * @param[in]     batch_offset    The offset on axis # 3.
+     * @param[in,out] output          Output tensor. Data types supported: Same as @p input.
+     *
+     * @note: The output tensor's low two dimensions can't be smaller than the input one's.
+     * @note: The gaps between the two lowest dimensions of input and output need to be divisible by 2.
+     *
+     */
+    void configure(CLCompileContext &compile_context, const ICLTensor *input, unsigned int batch_offset, ICLTensor *output);
     /**  Static function to check if given info will lead to a valid configuration of @ref CLBatchConcatenateLayerKernel
      *
      * @param[in] input        Input tensor info. Data types supported: All.
diff --git a/arm_compute/core/CL/kernels/CLBatchNormalizationLayerKernel.h b/arm_compute/core/CL/kernels/CLBatchNormalizationLayerKernel.h
index 7afa0e2..564b216 100644
--- a/arm_compute/core/CL/kernels/CLBatchNormalizationLayerKernel.h
+++ b/arm_compute/core/CL/kernels/CLBatchNormalizationLayerKernel.h
@@ -1,5 +1,5 @@
 /*
- * Copyright (c) 2017-2019 ARM Limited.
+ * Copyright (c) 2017-2020 ARM Limited.
  *
  * SPDX-License-Identifier: MIT
  *
@@ -65,6 +65,25 @@
      */
     void configure(ICLTensor *input, ICLTensor *output, const ICLTensor *mean, const ICLTensor *var, const ICLTensor *beta = nullptr, const ICLTensor *gamma = nullptr, float epsilon = 0.001f,
                    ActivationLayerInfo act_info = ActivationLayerInfo());
+    /** Set the input and output tensors.
+     *
+     * @note If the output tensor is a nullptr, the batch normalization function will be performed in-place
+     *
+     * @param[in]      compile_context The compile context to be used.
+     * @param[in, out] input           Source tensor. In case of @p output tensor = nullptr, this tensor will store the result.
+     *                                 3 lower dimensions represent a single input with dimensions [width, height, FM].
+     *                                 The rest are optional and used for representing batches. Data types supported: F16/F32. Data layouts supported: NCHW/NHWC.
+     * @param[out]     output          Destination tensor. Output will have the same number of dimensions as input. Data type supported: same as @p input
+     * @param[in]      mean            Mean values tensor. 1 dimension with size equal to the feature maps [FM]. Data types supported: Same as @p input
+     * @param[in]      var             Variance values tensor. 1 dimension with size equal to the feature maps [FM]. Data types supported: Same as @p input
+     * @param[in]      beta            (Optional) Beta values tensor info. 1 dimension with size equal to the feature maps [FM]. If not provided, default value for beta is 0. Data types supported: Same as @p input
+     * @param[in]      gamma           (Optional) Gamma values tensor info. 1 dimension with size equal to the feature maps [FM]. If not provided, default value for gamma is 1. Data types supported: Same as @p input
+     * @param[in]      epsilon         (Optional) Small value to avoid division with zero. Default value is 0.001f.
+     * @param[in]      act_info        (Optional) Activation layer information in case of a fused activation. Only RELU, BOUNDED_RELU and LU_BOUNDED_RELU supported.
+     */
+    void configure(CLCompileContext &compile_context, ICLTensor *input, ICLTensor *output, const ICLTensor *mean, const ICLTensor *var, const ICLTensor *beta = nullptr, const ICLTensor *gamma = nullptr,
+                   float               epsilon  = 0.001f,
+                   ActivationLayerInfo act_info = ActivationLayerInfo());
     /** Static function to check if given info will lead to a valid configuration of @ref CLBatchNormalizationLayerKernel
      *
      * @param[in] input    Source tensor info. In case of @p output tensor info = nullptr, this tensor will store the result.
diff --git a/arm_compute/core/CL/kernels/CLBatchToSpaceLayerKernel.h b/arm_compute/core/CL/kernels/CLBatchToSpaceLayerKernel.h
index 21197c2..f9289ea 100644
--- a/arm_compute/core/CL/kernels/CLBatchToSpaceLayerKernel.h
+++ b/arm_compute/core/CL/kernels/CLBatchToSpaceLayerKernel.h
@@ -54,6 +54,14 @@
      * @param[out] output      Tensor output. Data types supported: same as @p input
      */
     void configure(const ICLTensor *input, const ICLTensor *block_shape, ICLTensor *output);
+    /** Initialise the kernel's inputs and output.
+     *
+     * @param[in]  compile_context The compile context to be used.
+     * @param[in]  input           Tensor input. Supported tensor rank: 4. Data types supported: All.
+     * @param[in]  block_shape     1-D tensor with shape [M]. Data types supported: S32
+     * @param[out] output          Tensor output. Data types supported: same as @p input
+     */
+    void configure(CLCompileContext &compile_context, const ICLTensor *input, const ICLTensor *block_shape, ICLTensor *output);
     /** Initialise the kernel's inputs and output (Static block shape).
      *
      * @param[in]  input         Tensor input. Supported tensor rank: 4. Data types supported: All.
@@ -62,6 +70,15 @@
      * @param[out] output        Tensor output. Data types supported: same as @p input
      */
     void configure(const ICLTensor *input, const int32_t block_shape_x, const int32_t block_shape_y, ICLTensor *output);
+    /** Initialise the kernel's inputs and output (Static block shape).
+     *
+     * @param[in]  compile_context The compile context to be used.
+     * @param[in]  input           Tensor input. Supported tensor rank: 4. Data types supported: All.
+     * @param[in]  block_shape_x   Block shape x value.
+     * @param[in]  block_shape_y   Block shape y value.
+     * @param[out] output          Tensor output. Data types supported: same as @p input
+     */
+    void configure(CLCompileContext &compile_context, const ICLTensor *input, const int32_t block_shape_x, const int32_t block_shape_y, ICLTensor *output);
     /** Static function to check if given info will lead to a valid configuration of @ref CLBatchToSpaceLayerKernel
      *
      * @param[in] input       Tensor input. Supported tensor rank: 4. Data types supported: All.
diff --git a/arm_compute/core/CL/kernels/CLBitwiseAndKernel.h b/arm_compute/core/CL/kernels/CLBitwiseAndKernel.h
index 0aa2228..6c60bc0 100644
--- a/arm_compute/core/CL/kernels/CLBitwiseAndKernel.h
+++ b/arm_compute/core/CL/kernels/CLBitwiseAndKernel.h
@@ -1,5 +1,5 @@
 /*
- * Copyright (c) 2016-2019 ARM Limited.
+ * Copyright (c) 2016-2020 ARM Limited.
  *
  * SPDX-License-Identifier: MIT
  *
@@ -55,6 +55,14 @@
      * @param[out] output Destination tensor. Data types supported: U8.
      */
     void configure(const ICLTensor *input1, const ICLTensor *input2, ICLTensor *output);
+    /** Set the inputs and output images
+     *
+     * @param[in]  compile_context The compile context to be used.
+     * @param[in]  input1          Source tensor. Data types supported: U8.
+     * @param[in]  input2          Source tensor. Data types supported: U8.
+     * @param[out] output          Destination tensor. Data types supported: U8.
+     */
+    void configure(CLCompileContext &compile_context, const ICLTensor *input1, const ICLTensor *input2, ICLTensor *output);
 
     // Inherited methods overridden:
     void run(const Window &window, cl::CommandQueue &queue) override;
diff --git a/arm_compute/core/CL/kernels/CLBitwiseNotKernel.h b/arm_compute/core/CL/kernels/CLBitwiseNotKernel.h
index a7b00dd..0522841 100644
--- a/arm_compute/core/CL/kernels/CLBitwiseNotKernel.h
+++ b/arm_compute/core/CL/kernels/CLBitwiseNotKernel.h
@@ -1,5 +1,5 @@
 /*
- * Copyright (c) 2016-2019 ARM Limited.
+ * Copyright (c) 2016-2020 ARM Limited.
  *
  * SPDX-License-Identifier: MIT
  *
@@ -44,6 +44,13 @@
      * @param[out] output Destination tensor. Data types supported: U8.
      */
     void configure(const ICLTensor *input, ICLTensor *output);
+    /** Set the inputs and output images.
+     *
+     * @param[in]  compile_context The compile context to be used.
+     * @param[in]  input           Source tensor. Data types supported: U8.
+     * @param[out] output          Destination tensor. Data types supported: U8.
+     */
+    void configure(CLCompileContext &compile_context, const ICLTensor *input, ICLTensor *output);
 };
 } // namespace arm_compute
 #endif /* ARM_COMPUTE_CLBITWISENOTKERNEL_H */
diff --git a/arm_compute/core/CL/kernels/CLBitwiseOrKernel.h b/arm_compute/core/CL/kernels/CLBitwiseOrKernel.h
index 5764cf5..151f19d 100644
--- a/arm_compute/core/CL/kernels/CLBitwiseOrKernel.h
+++ b/arm_compute/core/CL/kernels/CLBitwiseOrKernel.h
@@ -1,5 +1,5 @@
 /*
- * Copyright (c) 2016-2019 ARM Limited.
+ * Copyright (c) 2016-2020 ARM Limited.
  *
  * SPDX-License-Identifier: MIT
  *
@@ -55,6 +55,14 @@
      * @param[out] output Destination tensor. Data types supported: U8.
      */
     void configure(const ICLTensor *input1, const ICLTensor *input2, ICLTensor *output);
+    /** Set the inputs and output images
+     *
+     * @param[in]  compile_context The compile context to be used.
+     * @param[in]  input1          Source tensor. Data types supported: U8.
+     * @param[in]  input2          Source tensor. Data types supported: U8.
+     * @param[out] output          Destination tensor. Data types supported: U8.
+     */
+    void configure(CLCompileContext &compile_context, const ICLTensor *input1, const ICLTensor *input2, ICLTensor *output);
 
     // Inherited methods overridden:
     void run(const Window &window, cl::CommandQueue &queue) override;
diff --git a/arm_compute/core/CL/kernels/CLBitwiseXorKernel.h b/arm_compute/core/CL/kernels/CLBitwiseXorKernel.h
index c1e2e4b..03c1e05 100644
--- a/arm_compute/core/CL/kernels/CLBitwiseXorKernel.h
+++ b/arm_compute/core/CL/kernels/CLBitwiseXorKernel.h
@@ -1,5 +1,5 @@
 /*
- * Copyright (c) 2016-2019 ARM Limited.
+ * Copyright (c) 2016-2020 ARM Limited.
  *
  * SPDX-License-Identifier: MIT
  *
@@ -55,6 +55,14 @@
      * @param[out] output Destination tensor. Data types supported: U8.
      */
     void configure(const ICLTensor *input1, const ICLTensor *input2, ICLTensor *output);
+    /** Set the inputs and output images
+     *
+     * @param[in]  compile_context The compile context to be used.
+     * @param[in]  input1          Source tensor. Data types supported: U8.
+     * @param[in]  input2          Source tensor. Data types supported: U8.
+     * @param[out] output          Destination tensor. Data types supported: U8.
+     */
+    void configure(CLCompileContext &compile_context, const ICLTensor *input1, const ICLTensor *input2, ICLTensor *output);
 
     // Inherited methods overridden:
     void run(const Window &window, cl::CommandQueue &queue) override;
diff --git a/arm_compute/core/CL/kernels/CLBoundingBoxTransformKernel.h b/arm_compute/core/CL/kernels/CLBoundingBoxTransformKernel.h
index bd16455..ffa63bd 100644
--- a/arm_compute/core/CL/kernels/CLBoundingBoxTransformKernel.h
+++ b/arm_compute/core/CL/kernels/CLBoundingBoxTransformKernel.h
@@ -1,5 +1,5 @@
 /*
- * Copyright (c) 2018-2019 ARM Limited.
+ * Copyright (c) 2018-2020 ARM Limited.
  *
  * SPDX-License-Identifier: MIT
  *
@@ -59,6 +59,19 @@
      *
      */
     void configure(const ICLTensor *boxes, ICLTensor *pred_boxes, const ICLTensor *deltas, const BoundingBoxTransformInfo &info);
+    /** Set the input and output tensors.
+     *
+     * @param[in]  compile_context The compile context to be used.
+     * @param[in]  boxes           Source tensor. Bounding box proposals in pixel coordinates. Size(M, 4), format [x1, y1, x2, y2]. Data types supported: QASYMM16/F16/F32.
+     * @param[out] pred_boxes      Destination tensor. Pixel coordinates of the transformed bounding boxes. Size (M, 4*K), format [x1, y1, x2, y2]. Data types supported: Same as @p input
+     * @param[in]  deltas          Bounding box translations and scales. Size (M, 4*K), format [dx, dy, dw, dh], K  is the number of classes.
+     *                             Data types supported: QASYMM8 if @p input is QASYMM16, otherwise same as @p input
+     * @param[in]  info            Contains BoundingBox operation information described in @ref BoundingBoxTransformInfo.
+     *
+     * @note Only single image prediction is supported. Height and Width (and scale) of the image will be contained in the BoundingBoxTransformInfo struct.
+     *
+     */
+    void configure(CLCompileContext &compile_context, const ICLTensor *boxes, ICLTensor *pred_boxes, const ICLTensor *deltas, const BoundingBoxTransformInfo &info);
 
     /** Static function to check if given info will lead to a valid configuration of @ref CLBoundingBoxTransform
      *
diff --git a/arm_compute/core/CL/kernels/CLBox3x3Kernel.h b/arm_compute/core/CL/kernels/CLBox3x3Kernel.h
index 359b227..572ae87 100644
--- a/arm_compute/core/CL/kernels/CLBox3x3Kernel.h
+++ b/arm_compute/core/CL/kernels/CLBox3x3Kernel.h
@@ -1,5 +1,5 @@
 /*
- * Copyright (c) 2016-2019 ARM Limited.
+ * Copyright (c) 2016-2020 ARM Limited.
  *
  * SPDX-License-Identifier: MIT
  *
@@ -43,6 +43,14 @@
      * @param[in]  border_undefined True if the border mode is undefined. False if it's replicate or constant.
      */
     void configure(const ICLTensor *input, ICLTensor *output, bool border_undefined);
+    /**Initialise the kernel's input and output.
+     *
+     * @param[in]  compile_context  The compile context to be used.
+     * @param[in]  input            An input tensor. Data types supported: U8
+     * @param[out] output           The output tensor. Data types supported: U8.
+     * @param[in]  border_undefined True if the border mode is undefined. False if it's replicate or constant.
+     */
+    void configure(CLCompileContext &compile_context, const ICLTensor *input, ICLTensor *output, bool border_undefined);
 
     //Inherited methods overriden:
     BorderSize border_size() const override;
diff --git a/arm_compute/core/CL/kernels/CLCannyEdgeKernel.h b/arm_compute/core/CL/kernels/CLCannyEdgeKernel.h
index 2d348dd..67c23dd 100644
--- a/arm_compute/core/CL/kernels/CLCannyEdgeKernel.h
+++ b/arm_compute/core/CL/kernels/CLCannyEdgeKernel.h
@@ -1,5 +1,5 @@
 /*
- * Copyright (c) 2017-2019 ARM Limited.
+ * Copyright (c) 2017-2020 ARM Limited.
  *
  * SPDX-License-Identifier: MIT
  *
@@ -54,6 +54,18 @@
      * @param[in]  norm_type Normalization type. if 1, L1-Norm otherwise L2-Norm.
      */
     void configure(const ICLTensor *gx, const ICLTensor *gy, ICLTensor *magnitude, ICLTensor *phase, int32_t norm_type);
+    /** Initialise the kernel's sources, destinations and border mode.
+     *
+     * @note gx, gy and mag must all be the same size (either 16 or 32).
+     *
+     * @param[in]  compile_context The compile context to be used.
+     * @param[in]  gx              Source tensor - Gx component. Data types supported: S16/S32.
+     * @param[in]  gy              Source tensor - Gy component. Data types supported: Same as gx.
+     * @param[out] magnitude       Destination tensor - Magnitude. Data types supported: U16/U32. Must match the pixel size of gx, gy.
+     * @param[out] phase           Destination tensor - Quantized phase. Data types supported: U8.
+     * @param[in]  norm_type       Normalization type. if 1, L1-Norm otherwise L2-Norm.
+     */
+    void configure(CLCompileContext &compile_context, const ICLTensor *gx, const ICLTensor *gy, ICLTensor *magnitude, ICLTensor *phase, int32_t norm_type);
 
     // Inherited methods overridden:
     void run(const Window &window, cl::CommandQueue &queue) override;
@@ -90,6 +102,16 @@
      * @param[in]  border_undefined True if the border mode is undefined. False if it's replicate or constant.
      */
     void configure(const ICLTensor *magnitude, const ICLTensor *phase, ICLTensor *output, int32_t lower_thr, bool border_undefined);
+    /** Initialise the kernel's sources, destination and border mode.
+     *
+     * @param[in]  compile_context  The compile context to be used.
+     * @param[in]  magnitude        Source tensor - Magnitude. Data types supported: U16/U32.
+     * @param[in]  phase            Source tensor - Quantized phase. Data types supported: U8.
+     * @param[out] output           Destination tensor. Data types supported: U16/U32.
+     * @param[in]  lower_thr        Lower threshold.
+     * @param[in]  border_undefined True if the border mode is undefined. False if it's replicate or constant.
+     */
+    void configure(CLCompileContext &compile_context, const ICLTensor *magnitude, const ICLTensor *phase, ICLTensor *output, int32_t lower_thr, bool border_undefined);
 
     // Inherited methods overridden:
     void run(const Window &window, cl::CommandQueue &queue) override;
@@ -129,6 +151,24 @@
      */
     void configure(const ICLTensor *input, ICLTensor *output, int32_t upper_thr, int32_t lower_thr,
                    ICLTensor *visited, ICLTensor *recorded, ICLTensor *l1_stack, ICLTensor *l1_stack_counter);
+    /** Initialise the kernel's source, destination and border mode.
+     *
+     * @param[in]     compile_context  The compile context to be used.
+     * @param[in]     input            Source tensor. Data types supported: U8.
+     * @param[out]    output           Destination tensor. Data types supported: U8.
+     * @param[in]     upper_thr        Upper threshold used for the hysteresis
+     * @param[in]     lower_thr        Lower threshold used for the hysteresis
+     * @param[in,out] visited          Tensor for keeping the visited pixels. Data types supported: U32.
+     *                                 Expected to be initialized to 0 before each run.
+     * @param[in,out] recorded         Tensor for keeping the recorded pixels. Data types supported: U32
+     *                                 Expected to be initialized to 0 before each run.
+     * @param[in,out] l1_stack         Tensor with the L1 stack for each pixel. Data types supported: S32.
+     *                                 Expected to be initialized to 0 before each run.
+     * @param[in,out] l1_stack_counter Tensor for counting the elements in the L1 stack of each pixel. Data types supported: U8.
+     *                                              Expected to be initialized to 0 before each run.
+     */
+    void configure(CLCompileContext &compile_context, const ICLTensor *input, ICLTensor *output, int32_t upper_thr, int32_t lower_thr,
+                   ICLTensor *visited, ICLTensor *recorded, ICLTensor *l1_stack, ICLTensor *l1_stack_counter);
 
     // Inherited methods overridden:
     void run(const Window &window, cl::CommandQueue &queue) override;
diff --git a/arm_compute/core/CL/kernels/CLChannelCombineKernel.h b/arm_compute/core/CL/kernels/CLChannelCombineKernel.h
index ae5658f..60d0bd4 100644
--- a/arm_compute/core/CL/kernels/CLChannelCombineKernel.h
+++ b/arm_compute/core/CL/kernels/CLChannelCombineKernel.h
@@ -1,5 +1,5 @@
 /*
- * Copyright (c) 2016-2019 ARM Limited.
+ * Copyright (c) 2016-2020 ARM Limited.
  *
  * SPDX-License-Identifier: MIT
  *
@@ -62,12 +62,31 @@
     void configure(const ICLTensor *plane0, const ICLTensor *plane1, const ICLTensor *plane2, const ICLTensor *plane3, ICLTensor *output);
     /** Configure function's inputs and outputs.
      *
+     * @param[in]  compile_context The compile context to be used.
+     * @param[in]  plane0          The 2D plane that forms channel 0. Must be of U8 format.
+     * @param[in]  plane1          The 2D plane that forms channel 1. Must be of U8 format.
+     * @param[in]  plane2          The 2D plane that forms channel 2. Must be of U8 format.
+     * @param[in]  plane3          The 2D plane that forms channel 3. Must be of U8 format.
+     * @param[out] output          The single planar output tensor.
+     */
+    void configure(CLCompileContext &compile_context, const ICLTensor *plane0, const ICLTensor *plane1, const ICLTensor *plane2, const ICLTensor *plane3, ICLTensor *output);
+    /** Configure function's inputs and outputs.
+     *
      * @param[in]  plane0 The 2D plane that forms channel 0. Must be of U8 format.
      * @param[in]  plane1 The 2D plane that forms channel 1. Must be of U8 format.
      * @param[in]  plane2 The 2D plane that forms channel 2. Must be of U8 format.
      * @param[out] output The multi planar output tensor.
      */
     void configure(const ICLImage *plane0, const ICLImage *plane1, const ICLImage *plane2, ICLMultiImage *output);
+    /** Configure function's inputs and outputs.
+     *
+     * @param[in]  compile_context The compile context to be used.
+     * @param[in]  plane0          The 2D plane that forms channel 0. Must be of U8 format.
+     * @param[in]  plane1          The 2D plane that forms channel 1. Must be of U8 format.
+     * @param[in]  plane2          The 2D plane that forms channel 2. Must be of U8 format.
+     * @param[out] output          The multi planar output tensor.
+     */
+    void configure(CLCompileContext &compile_context, const ICLImage *plane0, const ICLImage *plane1, const ICLImage *plane2, ICLMultiImage *output);
 
     // Inherited methods overridden:
     void run(const Window &window, cl::CommandQueue &queue) override;
diff --git a/arm_compute/core/CL/kernels/CLChannelExtractKernel.h b/arm_compute/core/CL/kernels/CLChannelExtractKernel.h
index 371f17f..1f2cc89 100644
--- a/arm_compute/core/CL/kernels/CLChannelExtractKernel.h
+++ b/arm_compute/core/CL/kernels/CLChannelExtractKernel.h
@@ -1,5 +1,5 @@
 /*
- * Copyright (c) 2016-2019 ARM Limited.
+ * Copyright (c) 2016-2020 ARM Limited.
  *
  * SPDX-License-Identifier: MIT
  *
@@ -60,11 +60,27 @@
     void configure(const ICLTensor *input, Channel channel, ICLTensor *output);
     /** Set the input and output of the kernel
      *
+     * @param[in]  compile_context The compile context to be used.
+     * @param[in]  input           Source tensor. Formats supported: RGB888/RGBA8888/YUYV422/UYVY422
+     * @param[in]  channel         Channel to extract.
+     * @param[out] output          Destination tensor. Must be of U8 format.
+     */
+    void configure(CLCompileContext &compile_context, const ICLTensor *input, Channel channel, ICLTensor *output);
+    /** Set the input and output of the kernel
+     *
      * @param[in]  input   Multi-planar source image. Formats supported: NV12/NV21/IYUV/YUV444
      * @param[in]  channel Channel to extract.
      * @param[out] output  Single-planar 2D destination image. Must be of U8 format.
      */
     void configure(const ICLMultiImage *input, Channel channel, ICLImage *output);
+    /** Set the input and output of the kernel
+     *
+     * @param[in]  compile_context The compile context to be used.
+     * @param[in]  input           Multi-planar source image. Formats supported: NV12/NV21/IYUV/YUV444
+     * @param[in]  channel         Channel to extract.
+     * @param[out] output          Single-planar 2D destination image. Must be of U8 format.
+     */
+    void configure(CLCompileContext &compile_context, const ICLMultiImage *input, Channel channel, ICLImage *output);
 
     // Inherited methods overridden:
     void run(const Window &window, cl::CommandQueue &queue) override;
diff --git a/arm_compute/core/CL/kernels/CLChannelShuffleLayerKernel.h b/arm_compute/core/CL/kernels/CLChannelShuffleLayerKernel.h
index 7e6589e..921c20d 100644
--- a/arm_compute/core/CL/kernels/CLChannelShuffleLayerKernel.h
+++ b/arm_compute/core/CL/kernels/CLChannelShuffleLayerKernel.h
@@ -53,6 +53,14 @@
      * @param[in]  num_groups Number of groups. Must be greater than 1 and the number of channels of the tensors must be a multiple of the number of groups.
      */
     void configure(const ICLTensor *input, ICLTensor *output, unsigned int num_groups);
+    /** Configure function's inputs and outputs.
+     *
+     * @param[in]  compile_context The compile context to be used.
+     * @param[in]  input           Input tensor. Data types supported: All.
+     * @param[out] output          Output tensor. Data type supported: Same as @p input
+     * @param[in]  num_groups      Number of groups. Must be greater than 1 and the number of channels of the tensors must be a multiple of the number of groups.
+     */
+    void configure(CLCompileContext &compile_context, const ICLTensor *input, ICLTensor *output, unsigned int num_groups);
     /** Static function to check if given info will lead to a valid configuration of @ref CLChannelShuffleLayerKernel
      *
      * @param[in] input      Input tensor info. Data types supported: All.
diff --git a/arm_compute/core/CL/kernels/CLCol2ImKernel.h b/arm_compute/core/CL/kernels/CLCol2ImKernel.h
index b22c666..6ef4248 100644
--- a/arm_compute/core/CL/kernels/CLCol2ImKernel.h
+++ b/arm_compute/core/CL/kernels/CLCol2ImKernel.h
@@ -72,6 +72,16 @@
      * @param[in]  num_groups     (Optional) Number of groups when performing a grouped convolution
      */
     void configure(const ICLTensor *input, ICLTensor *output, const Size2D &convolved_dims, unsigned int num_groups = 1);
+    /** Set the input and output of the kernel.
+     *
+     * @param[in]  compile_context The compile context to be used.
+     * @param[in]  input           The input tensor to convert. Data types supported: QASYMM8/QASYMM8_SIGNED/F16/F32
+     * @param[out] output          The output tensor. 3 lower dimensions represent a single output [width, height, OFM],
+     *                             while the rest represent batch of outputs. Data types supported: Same as @p input. Data layout: NCHW
+     * @param[in]  convolved_dims  Output convolved dimensions.
+     * @param[in]  num_groups      (Optional) Number of groups when performing a grouped convolution
+     */
+    void configure(CLCompileContext &compile_context, const ICLTensor *input, ICLTensor *output, const Size2D &convolved_dims, unsigned int num_groups = 1);
     /** Static function to check if given info will lead to a valid configuration of @ref CLCol2ImKernel
      *
      * @param[in] input          The input tensor to convert. Data types supported: QASYMM8/QASYMM8_SIGNED/F16/F32
diff --git a/arm_compute/core/CL/kernels/CLColorConvertKernel.h b/arm_compute/core/CL/kernels/CLColorConvertKernel.h
index 2e23a62..25b95eb 100644
--- a/arm_compute/core/CL/kernels/CLColorConvertKernel.h
+++ b/arm_compute/core/CL/kernels/CLColorConvertKernel.h
@@ -1,5 +1,5 @@
 /*
- * Copyright (c) 2016-2019 ARM Limited.
+ * Copyright (c) 2016-2020 ARM Limited.
  *
  * SPDX-License-Identifier: MIT
  *
@@ -61,22 +61,52 @@
     void configure(const ICLTensor *input, ICLTensor *output);
     /** Set the input and output of the kernel
      *
+     * @param[in]  compile_context The compile context to be used.
+     * @param[in]  input           Source tensor. Formats supported: RGBA8888/UYVY422/YUYV422/RGB888
+     * @param[out] output          Destination tensor. Formats supported: RGB888 (if the formats of @p input are RGBA8888/UYVY422/YUYV422),
+     *                                                          RGBA8888 (if the formats of @p input are UYVY422/YUYV422/RGB888/),
+     *                                                          U8 (if the formats of @p input is RGB888)
+     */
+    void configure(CLCompileContext &compile_context, const ICLTensor *input, ICLTensor *output);
+    /** Set the input and output of the kernel
+     *
      * @param[in]  input  Multi-planar source image. Formats supported: NV12/NV21/IYUV
      * @param[out] output Single-planar destination image. Formats supported: RGB888/RGBA8888
      */
     void configure(const ICLMultiImage *input, ICLImage *output);
     /** Set the input and output of the kernel
      *
+     * @param[in]  compile_context The compile context to be used.
+     * @param[in]  input           Multi-planar source image. Formats supported: NV12/NV21/IYUV
+     * @param[out] output          Single-planar destination image. Formats supported: RGB888/RGBA8888
+     */
+    void configure(CLCompileContext &compile_context, const ICLMultiImage *input, ICLImage *output);
+    /** Set the input and output of the kernel
+     *
      * @param[in]  input  Single-planar source image. Formats supported: RGB888/RGBA8888/UYVY422/YUYV422
      * @param[out] output Multi-planar destination image. Formats supported: NV12/IYUV/YUV444 (if the formats of @p input are RGB888/RGB8888)
      */
     void configure(const ICLImage *input, ICLMultiImage *output);
     /** Set the input and output of the kernel
      *
+     * @param[in]  compile_context The compile context to be used.
+     * @param[in]  input           Single-planar source image. Formats supported: RGB888/RGBA8888/UYVY422/YUYV422
+     * @param[out] output          Multi-planar destination image. Formats supported: NV12/IYUV/YUV444 (if the formats of @p input are RGB888/RGB8888)
+     */
+    void configure(CLCompileContext &compile_context, const ICLImage *input, ICLMultiImage *output);
+    /** Set the input and output of the kernel
+     *
      * @param[in]  input  Multi-planar source image. Formats supported: NV12/NV21/IYUV
      * @param[out] output Multi-planar destination image. Formats supported: YUV444/IYUV (if the formats of @p input are NV12/NV21)/NV12 (if the format of  @p input is IYUV)
      */
     void configure(const ICLMultiImage *input, ICLMultiImage *output);
+    /** Set the input and output of the kernel
+     *
+     * @param[in]  compile_context The compile context to be used.
+     * @param[in]  input           Multi-planar source image. Formats supported: NV12/NV21/IYUV
+     * @param[out] output          Multi-planar destination image. Formats supported: YUV444/IYUV (if the formats of @p input are NV12/NV21)/NV12 (if the format of  @p input is IYUV)
+     */
+    void configure(CLCompileContext &compile_context, const ICLMultiImage *input, ICLMultiImage *output);
 
     // Inherited methods overridden:
     void run(const Window &window, cl::CommandQueue &queue) override;
diff --git a/arm_compute/core/CL/kernels/CLComparisonKernel.h b/arm_compute/core/CL/kernels/CLComparisonKernel.h
index a9c4639..1577993 100644
--- a/arm_compute/core/CL/kernels/CLComparisonKernel.h
+++ b/arm_compute/core/CL/kernels/CLComparisonKernel.h
@@ -56,6 +56,15 @@
      * @param[in]  operation Comparison operation to use.
      */
     void configure(const ICLTensor *input1, const ICLTensor *input2, ICLTensor *output, ComparisonOperation operation);
+    /** Set the inputs and output tensors
+     *
+     * @param[in]  compile_context The compile context to be used.
+     * @param[in]  input1          Source tensor. Data types supported: All.
+     * @param[in]  input2          Source tensor. Data types supported: Same as @p input1.
+     * @param[out] output          Destination tensor. Data types supported: U8.
+     * @param[in]  operation       Comparison operation to use.
+     */
+    void configure(CLCompileContext &compile_context, const ICLTensor *input1, const ICLTensor *input2, ICLTensor *output, ComparisonOperation operation);
     /** Static function to check if given info will lead to a valid configuration of @ref CLComparisonKernel
      *
      * @param[in] input1    Source tensor. Data types supported: All.
diff --git a/arm_compute/core/CL/kernels/CLConvertFullyConnectedWeightsKernel.h b/arm_compute/core/CL/kernels/CLConvertFullyConnectedWeightsKernel.h
index b204eaa..f7e212e 100644
--- a/arm_compute/core/CL/kernels/CLConvertFullyConnectedWeightsKernel.h
+++ b/arm_compute/core/CL/kernels/CLConvertFullyConnectedWeightsKernel.h
@@ -61,6 +61,15 @@
      * @param[in]  data_layout          The data layout the weights have been trained in.
      */
     void configure(const ICLTensor *input, ICLTensor *output, const TensorShape &original_input_shape, DataLayout data_layout);
+    /** Set the input and output tensor.
+     *
+     * @param[in]  compile_context      The compile context to be used.
+     * @param[in]  input                Source weights tensor to convert. Must be 2 dimensional. Data types supported: All.
+     * @param[out] output               The converted weights tensor. Shape and Data Type: Same as @p input.
+     * @param[in]  original_input_shape Shape of the original input tensor (the one entering fully connected layer).
+     * @param[in]  data_layout          The data layout the weights have been trained in.
+     */
+    void configure(CLCompileContext &compile_context, const ICLTensor *input, ICLTensor *output, const TensorShape &original_input_shape, DataLayout data_layout);
     /** Static function to check if given info will lead to a valid configuration of @ref CLConvertFullyConnectedWeightsKernel
      *
      * @param[in] input                Source weights tensor info to convert. Must be 2 dimensional. Data types supported: All.
diff --git a/arm_compute/core/CL/kernels/CLConvolutionKernel.h b/arm_compute/core/CL/kernels/CLConvolutionKernel.h
index 089a8cd..e1cdc88 100644
--- a/arm_compute/core/CL/kernels/CLConvolutionKernel.h
+++ b/arm_compute/core/CL/kernels/CLConvolutionKernel.h
@@ -1,5 +1,5 @@
 /*
- * Copyright (c) 2016-2019 ARM Limited.
+ * Copyright (c) 2016-2020 ARM Limited.
  *
  * SPDX-License-Identifier: MIT
  *
@@ -61,6 +61,16 @@
      * @param[in]  border_undefined True if the border mode is undefined. False if it's replicate or constant.
      */
     void configure(const ICLTensor *input, ICLTensor *output, const int16_t *conv, uint32_t scale, bool border_undefined);
+    /** Initialise the kernel's input, output and border mode.
+     *
+     * @param[in]  compile_context  The compile context to be used.
+     * @param[in]  input            Source tensor. Data types supported: U8.
+     * @param[out] output           Destination tensor, Data types supported: U8, S16.
+     * @param[in]  conv             Convolution matrix to apply to the input tensor.
+     * @param[in]  scale            Scale of the convolution matrix. If 0 is passed, it will be set to the sum of the coefficients of the convolution or 1 if they add up to 0.
+     * @param[in]  border_undefined True if the border mode is undefined. False if it's replicate or constant.
+     */
+    void configure(CLCompileContext &compile_context, const ICLTensor *input, ICLTensor *output, const int16_t *conv, uint32_t scale, bool border_undefined);
 
     // Inherited methods overridden:
     BorderSize border_size() const override;
@@ -94,6 +104,15 @@
      * @param[in]  border_undefined True if the border mode is undefined. False if it's replicate or constant.
      */
     void configure(const ICLTensor *input, ICLTensor *output, const int16_t *conv, bool border_undefined);
+    /** Initialise the kernel's input, output and border mode.
+     *
+     * @param[in]  compile_context  The compile context to be used.
+     * @param[in]  input            Source tensor. Data types supported: U8.
+     * @param[out] output           Destination tensor, Data types supported: S16.
+     * @param[in]  conv             Convolution matrix to apply to the input tensor.
+     * @param[in]  border_undefined True if the border mode is undefined. False if it's replicate or constant.
+     */
+    void configure(CLCompileContext &compile_context, const ICLTensor *input, ICLTensor *output, const int16_t *conv, bool border_undefined);
 
     // Inherited methods overridden:
     BorderSize border_size() const override;
@@ -124,6 +143,17 @@
      * @param[in]  data_type        Data type to use for intermeidate result. @sa data_type_for_convolution
      */
     void configure(const ICLTensor *input, ICLTensor *output, const int16_t *conv, uint32_t scale, bool border_undefined, DataType data_type = DataType::S32);
+    /** Initialise the kernel's input, output and border mode.
+     *
+     * @param[in]  compile_context  The compile context to be used.
+     * @param[in]  input            Source tensor. Data types supported: S16.
+     * @param[out] output           Destination tensor, Data types supported: U8, S16.
+     * @param[in]  conv             Convolution matrix to apply to the input tensor.
+     * @param[in]  scale            Scale of the convolution matrix.
+     * @param[in]  border_undefined True if the border mode is undefined. False if it's replicate or constant.
+     * @param[in]  data_type        Data type to use for intermeidate result. @sa data_type_for_convolution
+     */
+    void configure(CLCompileContext &compile_context, const ICLTensor *input, ICLTensor *output, const int16_t *conv, uint32_t scale, bool border_undefined, DataType data_type = DataType::S32);
 
     // Inherited methods overridden:
     BorderSize border_size() const override;
@@ -168,6 +198,18 @@
      * @param[in]  border_undefined True if the border mode is undefined. False if it's replicate or constant.
      */
     void configure(const ICLTensor *input, ICLTensor *output, const int16_t *conv, uint32_t width, uint32_t height, uint32_t scale, bool border_undefined);
+    /** Initialise the kernel's input, output and border mode.
+     *
+     * @param[in]  compile_context  The compile context to be used.
+     * @param[in]  input            Source tensor. Data types supported: U8.
+     * @param[out] output           Destination tensor, Data types supported: U8, S16.
+     * @param[in]  conv             Convolution matrix to apply to the input tensor.
+     * @param[in]  width            Width of convolution matrix (Number of columns)
+     * @param[in]  height           Height of convolution matrix (Number of rows)
+     * @param[in]  scale            Scale of the convolution matrix. If 0 is passed, it will be set to the sum of the coefficients of the convolution or 1 if they add up to 0.
+     * @param[in]  border_undefined True if the border mode is undefined. False if it's replicate or constant.
+     */
+    void configure(CLCompileContext &compile_context, const ICLTensor *input, ICLTensor *output, const int16_t *conv, uint32_t width, uint32_t height, uint32_t scale, bool border_undefined);
 
     // Inherited methods overridden:
     void run(const Window &window, cl::CommandQueue &queue) override;
diff --git a/arm_compute/core/CL/kernels/CLCopyKernel.h b/arm_compute/core/CL/kernels/CLCopyKernel.h
index 50bf389..1774f8c 100644
--- a/arm_compute/core/CL/kernels/CLCopyKernel.h
+++ b/arm_compute/core/CL/kernels/CLCopyKernel.h
@@ -1,5 +1,5 @@
 /*
- * Copyright (c) 2018-2019 ARM Limited.
+ * Copyright (c) 2018-2020 ARM Limited.
  *
  * SPDX-License-Identifier: MIT
  *
@@ -53,6 +53,15 @@
      * @param[in]  output_window (Optional) Window to be used in case only copying into part of a tensor. Default is nullptr.
      */
     void configure(const ICLTensor *input, ICLTensor *output, const PaddingList &padding = PaddingList(), Window *output_window = nullptr);
+    /** Initialize the kernel's input, output.
+     *
+     * @param[in]  compile_context The compile context to be used.
+     * @param[in]  input           Source tensor. Data types supported: U8/S8/QASYMM8/U16/S16/F16/U32/S32/F32.
+     * @param[out] output          Destination tensor. Data types supported: same as @p input.
+     * @param[in]  padding         (Optional) Padding to be applied to the input tensor
+     * @param[in]  output_window   (Optional) Window to be used in case only copying into part of a tensor. Default is nullptr.
+     */
+    void configure(CLCompileContext &compile_context, const ICLTensor *input, ICLTensor *output, const PaddingList &padding = PaddingList(), Window *output_window = nullptr);
     /** Static function to check if given info will lead to a valid configuration of @ref CLCopyKernel
      *
      * @param[in] input         Source tensor info. Data types supported: U8/S8/QASYMM8/U16/S16/F16/U32/S32/F32.
diff --git a/arm_compute/core/CL/kernels/CLCropKernel.h b/arm_compute/core/CL/kernels/CLCropKernel.h
index bcce9c1..103986a 100644
--- a/arm_compute/core/CL/kernels/CLCropKernel.h
+++ b/arm_compute/core/CL/kernels/CLCropKernel.h
@@ -1,5 +1,5 @@
 /*
- * Copyright (c) 2019 ARM Limited.
+ * Copyright (c) 2019-2020 ARM Limited.
  *
  * SPDX-License-Identifier: MIT
  *
@@ -58,6 +58,21 @@
      * @param[in]  output_window       Output window to be used in case cropped image is being copied into a tensor. Default is nullptr.
      */
     void configure(const ICLTensor *input, ICLTensor *output, Coordinates2D start, Coordinates2D end, uint32_t batch_index, float extrapolation_value = 0, Window *output_window = nullptr);
+    /** Configure kernel
+     *
+     * @note Supported tensor rank: up to 4
+     *
+     * @param[in]  compile_context     The compile context to be used.
+     * @param[in]  input               Source tensor. Data type supported: U16/S16/U32/S32/F16/F32. Data layouts supported: NHWC.
+     * @param[out] output              Destination tensor. Data type supported: F32
+     * @param[in]  start               Coordinates of where to start cropping the image.
+     * @param[in]  end                 Coordinates of where to end cropping the image.
+     * @param[in]  batch_index         Fourth dimension index of the 3D image to crop in @p input.
+     * @param[in]  extrapolation_value Value to be used for values outside of the image. Default is 0.
+     * @param[in]  output_window       Output window to be used in case cropped image is being copied into a tensor. Default is nullptr.
+     */
+    void configure(CLCompileContext &compile_context, const ICLTensor *input, ICLTensor *output, Coordinates2D start, Coordinates2D end, uint32_t batch_index, float extrapolation_value = 0,
+                   Window *output_window = nullptr);
 
     /** Static function to check if given info will lead to a valid configuration of @ref CLStridedSliceKernel
      *
diff --git a/arm_compute/core/CL/kernels/CLDeconvolutionLayerUpsampleKernel.h b/arm_compute/core/CL/kernels/CLDeconvolutionLayerUpsampleKernel.h
index a1c6bbd..7e8a45f 100644
--- a/arm_compute/core/CL/kernels/CLDeconvolutionLayerUpsampleKernel.h
+++ b/arm_compute/core/CL/kernels/CLDeconvolutionLayerUpsampleKernel.h
@@ -55,6 +55,14 @@
      * @param[in]  info   Contains padding and stride information described in @ref PadStrideInfo.
      */
     void configure(const ICLTensor *input, ICLTensor *output, const PadStrideInfo &info);
+    /** Initialise the kernel's input and output.
+     *
+     * @param[in]  compile_context The compile context to be used.
+     * @param[in]  input           Source tensor. Data types supported: All.
+     * @param[out] output          Destination tensor. Data types supported: same as @p input. All but the lowest two dimensions must be the same size as in the input tensor, i.e. scaling is only performed within the XY-plane.
+     * @param[in]  info            Contains padding and stride information described in @ref PadStrideInfo.
+     */
+    void configure(CLCompileContext &compile_context, const ICLTensor *input, ICLTensor *output, const PadStrideInfo &info);
     /** Static function to check if given info will lead to a valid configuration of @ref CLDeconvolutionLayerUpsample
      *
      * @param[in] input  Source tensor info. Data types supported: All.
diff --git a/arm_compute/core/CL/kernels/CLDeconvolutionReshapeOutputKernel.h b/arm_compute/core/CL/kernels/CLDeconvolutionReshapeOutputKernel.h
index 6c90bd6..daeb8c1 100644
--- a/arm_compute/core/CL/kernels/CLDeconvolutionReshapeOutputKernel.h
+++ b/arm_compute/core/CL/kernels/CLDeconvolutionReshapeOutputKernel.h
@@ -68,6 +68,19 @@
      * @param[in]  deconv_info  Contains padding and policies to be used in the deconvolution, this is described in @ref PadStrideInfo. This kernel supports only stride_x = weights.width && stride_y = weights.height. Moreover, padding is not supported.
      */
     void configure(const ICLTensor *input, const ICLTensor *bias, ICLTensor *output, const ITensorInfo *input_info, const ITensorInfo *weights_info, const PadStrideInfo &deconv_info);
+    /** Initialise the kernel's source and destination.
+     *
+     * @param[in]  compile_context The compile context to be used.
+     * @param[in]  input           Input tensor. Supported data types: QASYMM8/QASYMM8_SIGNED/S32/F16/F32.
+     * @param[in]  bias            Bias tensor to be added directly during the reshape operation. Supported data types: same as @p input.  Supported data layouts: same as @p input.
+     * @param[out] output          Output tensor with the following shape: [stride_x * (input_width - 1) + filter_width - 2 * padx, stride_y * (input_height - 1) + filter_height - 2 * pady, ofms, batch_size]
+     *                             Supported data types: same as @p input.  Supported data layouts: same as @p input.
+     * @param[in]  input_info      Deconvolution input tensor info. Supported data types: same as @p input.  Supported data layouts: same as @p input.
+     * @param[in]  weights_info    Deconvolution weights tensor info. Supported data types: same as @p input.  Supported data layouts: same as @p input.
+     * @param[in]  deconv_info     Contains padding and policies to be used in the deconvolution, this is described in @ref PadStrideInfo. This kernel supports only stride_x = weights.width && stride_y = weights.height. Moreover, padding is not supported.
+     */
+    void configure(CLCompileContext &compile_context, const ICLTensor *input, const ICLTensor *bias, ICLTensor *output, const ITensorInfo *input_info, const ITensorInfo *weights_info,
+                   const PadStrideInfo &deconv_info);
 
     /** Static function to check if given info will lead to a valid configuration of @ref  CLDeconvolutionReshapeOutputKernel.
      *
diff --git a/arm_compute/core/CL/kernels/CLDepthConcatenateLayerKernel.h b/arm_compute/core/CL/kernels/CLDepthConcatenateLayerKernel.h
index e55dd5d..7b59441 100644
--- a/arm_compute/core/CL/kernels/CLDepthConcatenateLayerKernel.h
+++ b/arm_compute/core/CL/kernels/CLDepthConcatenateLayerKernel.h
@@ -61,6 +61,18 @@
      *
      */
     void configure(const ICLTensor *input, unsigned int depth_offset, ICLTensor *output);
+    /** Initialise the kernel's inputs and output
+     *
+     * @param[in]     compile_context The compile context to be used.
+     * @param[in]     input           Input tensor. Data types supported: QASYMM8/QASYMM8_SIGNED/F16/F32.
+     * @param[in]     depth_offset    The offset on the Z axis.
+     * @param[in,out] output          Output tensor. Data types supported: Same as @p input.
+     *
+     * @note: The output tensor's low two dimensions can't be smaller than the input one's.
+     * @note: The gaps between the two lowest dimensions of input and output need to be divisible by 2.
+     *
+     */
+    void configure(CLCompileContext &compile_context, const ICLTensor *input, unsigned int depth_offset, ICLTensor *output);
     /**  Static function to check if given info will lead to a valid configuration of @ref CLDepthConcatenateLayerKernel
      *
      * @param[in] input        Input tensor info. Data types supported: QASYMM8/QASYMM8_SIGNED/F16/F32
diff --git a/arm_compute/core/CL/kernels/CLDepthConvertLayerKernel.h b/arm_compute/core/CL/kernels/CLDepthConvertLayerKernel.h
index fb65aa5..8bbf9b3 100644
--- a/arm_compute/core/CL/kernels/CLDepthConvertLayerKernel.h
+++ b/arm_compute/core/CL/kernels/CLDepthConvertLayerKernel.h
@@ -1,5 +1,5 @@
 /*
- * Copyright (c) 2016-2019 ARM Limited.
+ * Copyright (c) 2016-2020 ARM Limited.
  *
  * SPDX-License-Identifier: MIT
  *
@@ -56,6 +56,26 @@
      * @param[in]  shift  Value for down/up conversions. Must be 0 <= shift < 8.
      */
     void configure(const ICLTensor *input, ICLTensor *output, ConvertPolicy policy, uint32_t shift);
+    /** Set the input and output of the kernel.
+     *
+     * Valid conversions Input -> Output :
+     *
+     *   - QSYMM8_PER_CHANNEL -> QASYMM8 (ATTENTION: it is the user's responsibility to keep track of the quantization info in the TensorInfo meta-data)
+     *   - U8  -> S8, U16, S16, U32, S32, F16, F32
+     *   - U16 -> U8, S8, S16, U32, S32, F16, F32
+     *   - S16 -> U8, S8, U16, U32, S32, F16, F32
+     *   - U32 -> U8, S8, U16, S16, S32, F16, F32
+     *   - S32 -> U8, S8, U16, S16, U32, F16, F32
+     *   - F16 -> U8, S8, U16, S16, U32, F32
+     *   - F32 -> U8, S8, U16, S16, U32, F16
+     *
+     * @param[in]  compile_context The compile context to be used.
+     * @param[in]  input           The input tensor to convert. Data types supported: U8/S8/QSYMM8_PER_CHANNEL/U16/S16/U32/S32/F16/F32.
+     * @param[out] output          The output tensor. Data types supported: U8/S8/QASYMM8/U16/S16/U32/S32/F16/F32.
+     * @param[in]  policy          Conversion policy
+     * @param[in]  shift           Value for down/up conversions. Must be 0 <= shift < 8.
+     */
+    void configure(CLCompileContext &compile_context, const ICLTensor *input, ICLTensor *output, ConvertPolicy policy, uint32_t shift);
     /** Static function to check if given info will lead to a valid configuration of @ref CLDepthConvertLayerKernel
      *
      * @param[in] input  Source tensor info. Data types supported: U8/S8/QSYMM8_PER_CHANNEL/U16/S16/U32/S32/F16/F32.
diff --git a/arm_compute/core/CL/kernels/CLDepthToSpaceLayerKernel.h b/arm_compute/core/CL/kernels/CLDepthToSpaceLayerKernel.h
index 637e5fa..541506b 100644
--- a/arm_compute/core/CL/kernels/CLDepthToSpaceLayerKernel.h
+++ b/arm_compute/core/CL/kernels/CLDepthToSpaceLayerKernel.h
@@ -54,6 +54,14 @@
      * @param[in]  block_shape Block shape value.
      */
     void configure(const ICLTensor *input, ICLTensor *output, int32_t block_shape);
+    /** Initialise the kernel's inputs and output.
+     *
+     * @param[in]  compile_context The compile context to be used.
+     * @param[in]  input           Tensor input. Supported tensor rank: 4. Data types supported: All.
+     * @param[out] output          Tensor output. Data types supported: same as @p input
+     * @param[in]  block_shape     Block shape value.
+     */
+    void configure(CLCompileContext &compile_context, const ICLTensor *input, ICLTensor *output, int32_t block_shape);
     /** Static function to check if given info will lead to a valid configuration of @ref CLDepthToSpaceLayerKernel.
      *
      * @param[in] input       Tensor input info. Supported tensor rank: 4. Data types supported: All.
diff --git a/arm_compute/core/CL/kernels/CLDepthwiseConvolutionLayer3x3NCHWKernel.h b/arm_compute/core/CL/kernels/CLDepthwiseConvolutionLayer3x3NCHWKernel.h
index 3d1b91c..f68fde4 100644
--- a/arm_compute/core/CL/kernels/CLDepthwiseConvolutionLayer3x3NCHWKernel.h
+++ b/arm_compute/core/CL/kernels/CLDepthwiseConvolutionLayer3x3NCHWKernel.h
@@ -1,5 +1,5 @@
 /*
- * Copyright (c) 2018-2019 ARM Limited.
+ * Copyright (c) 2018-2020 ARM Limited.
  *
  * SPDX-License-Identifier: MIT
  *
@@ -57,6 +57,27 @@
     void configure(const ICLTensor *input, const ICLTensor *weights, const ICLTensor *biases, ICLTensor *output, const PadStrideInfo &conv_info,
                    unsigned int depth_multiplier = 1, ActivationLayerInfo act_info = ActivationLayerInfo(), const Size2D &dilation = Size2D(1U, 1U),
                    const ICLTensor *output_multipliers = nullptr, const ICLTensor *output_shifts = nullptr) override;
+    /** Initialize the function's source, destination, conv and border_size.
+     *
+     * @param[in]  compile_context    The compile context to be used.
+     * @param[in]  input              Source tensor. DataType supported: QASYMM8/QASYMM8_SIGNED/F16/F32.
+     * @param[in]  weights            Weights tensor. A 3D tensor with dimensions [3, 3, IFM].
+     *                                Data type supported: Same as @p input or QASYMM8/QASYMM8_SIGNED/QSYMM8_PER_CHANNEL when @p input is QASYMM8/QASYMM8_SIGNED.
+     * @param[in]  biases             Biases tensor. A 1D tensor with dimensions [IFM]. Must be nullptr if not needed.
+     *                                Data type supported: Same as @p input, S32 when input is QASYMM8/QASYMM8_SIGNED.
+     * @param[out] output             Destination tensor. Data type supported: Same as @p input.
+     * @param[in]  conv_info          Padding and stride information to use for the convolution.
+     * @param[in]  depth_multiplier   (Optional) Multiplier to apply to the input's depth in order to retrieve the output's depth. Defaults to 1.
+     * @param[in]  act_info           (Optional) Activation layer information in case of a fused activation. Only RELU, BOUNDED_RELU and LU_BOUNDED_RELU for QASYMM8 supported.
+     * @param[in]  dilation           (Optional) Dilation, in elements, across x and y. Defaults to (1, 1).
+     * @param[in]  output_multipliers (Optional) Output multipliers tensor for quantized computations. In case of per-channel quantization,
+     *                                the number of multipliers must be equal to the number of filters (IFM). Supported data types: S32
+     * @param[in]  output_shifts      (Optional) Output shifts tensor for quantized computations. In case of per-channel quantization,
+     *                                the number of multipliers must be equal to the number of filters (IFM). Supported data types: S32
+     */
+    void configure(CLCompileContext &compile_context, const ICLTensor *input, const ICLTensor *weights, const ICLTensor *biases, ICLTensor *output, const PadStrideInfo &conv_info,
+                   unsigned int depth_multiplier = 1, ActivationLayerInfo act_info = ActivationLayerInfo(), const Size2D &dilation = Size2D(1U, 1U),
+                   const ICLTensor *output_multipliers = nullptr, const ICLTensor *output_shifts = nullptr) override;
     /** Static function to check if given info will lead to a valid configuration of @ref CLDepthwiseConvolutionLayer3x3NCHWKernel
      *
      * @param[in] input              Source tensor info. DataType supported: QASYMM8/QASYMM8_SIGNED/F16/F32.
diff --git a/arm_compute/core/CL/kernels/CLDepthwiseConvolutionLayer3x3NHWCKernel.h b/arm_compute/core/CL/kernels/CLDepthwiseConvolutionLayer3x3NHWCKernel.h
index 9e74be7..f9fda0a 100644
--- a/arm_compute/core/CL/kernels/CLDepthwiseConvolutionLayer3x3NHWCKernel.h
+++ b/arm_compute/core/CL/kernels/CLDepthwiseConvolutionLayer3x3NHWCKernel.h
@@ -1,5 +1,5 @@
 /*
- * Copyright (c) 2018-2019 ARM Limited.
+ * Copyright (c) 2018-2020 ARM Limited.
  *
  * SPDX-License-Identifier: MIT
  *
@@ -58,6 +58,27 @@
     void configure(const ICLTensor *input, const ICLTensor *weights, const ICLTensor *biases, ICLTensor *output, const PadStrideInfo &conv_info,
                    unsigned int depth_multiplier = 1, ActivationLayerInfo act_info = ActivationLayerInfo(), const Size2D &dilation = Size2D(1U, 1U),
                    const ICLTensor *output_multipliers = nullptr, const ICLTensor *output_shifts = nullptr) override;
+    /** Initialize the function's source, destination, conv and border_size.
+     *
+     * @param[in]  compile_context    The compile context to be used.
+     * @param[in]  input              Source tensor. DataType supported: QASYMM8/QASYMM8_SIGNED.
+     * @param[in]  weights            Weights tensor. A 3D tensor with dimensions [IFM, 3, 3].
+     *                                Data type supported: Same as @p input or QASYMM8/QASYMM8_SIGNED/QSYMM8_PER_CHANNEL when @p input is QASYMM8/QASYMM8_SIGNED.
+     * @param[in]  biases             Biases tensor. A 1D tensor with dimensions [IFM]. Must be nullptr if not needed.
+     *                                Data type supported: Same as @p input, S32 when input is QASYMM8/QASYMM8_SIGNED.
+     * @param[out] output             Destination tensor. Data type supported: Same as @p input.
+     * @param[in]  conv_info          Padding and stride information to use for the convolution.
+     * @param[in]  depth_multiplier   (Optional) Multiplier to apply to the input's depth in order to retrieve the output's depth. Defaults to 1.
+     * @param[in]  act_info           (Optional) Activation layer information in case of a fused activation. Only RELU, BOUNDED_RELU and LU_BOUNDED_RELU are supported.
+     * @param[in]  dilation           (Optional) Dilation, in elements, across x and y. Defaults to (1, 1).
+     * @param[in]  output_multipliers (Optional) Output multipliers tensor for quantized computations. In case of per-channel quantization,
+     *                                the number of multipliers must be equal to the number of filters (IFM). Supported data types: S32
+     * @param[in]  output_shifts      (Optional) Output shifts tensor for quantized computations. In case of per-channel quantization,
+     *                                the number of multipliers must be equal to the number of filters (IFM). Supported data types: S32
+     */
+    void configure(CLCompileContext &compile_context, const ICLTensor *input, const ICLTensor *weights, const ICLTensor *biases, ICLTensor *output, const PadStrideInfo &conv_info,
+                   unsigned int depth_multiplier = 1, ActivationLayerInfo act_info = ActivationLayerInfo(), const Size2D &dilation = Size2D(1U, 1U),
+                   const ICLTensor *output_multipliers = nullptr, const ICLTensor *output_shifts = nullptr) override;
     /** Static function to check if given info will lead to a valid configuration of @ref CLDepthwiseConvolutionLayer3x3NHWCKernel
      *
      * @param[in] input              Source tensor info. DataType supported: QASYMM8/QASYMM8_SIGNED.
diff --git a/arm_compute/core/CL/kernels/CLDepthwiseConvolutionLayerNativeKernel.h b/arm_compute/core/CL/kernels/CLDepthwiseConvolutionLayerNativeKernel.h
index 7e19ed6..db26b4a 100644
--- a/arm_compute/core/CL/kernels/CLDepthwiseConvolutionLayerNativeKernel.h
+++ b/arm_compute/core/CL/kernels/CLDepthwiseConvolutionLayerNativeKernel.h
@@ -68,6 +68,28 @@
     void configure(const ICLTensor *input, const ICLTensor *weights, const ICLTensor *biases, ICLTensor *output, const DWCWeightsKernelInfo &dwc_weights_info,
                    const DWCKernelInfo &dwc_info, const PadStrideInfo &conv_info, unsigned int depth_multiplier = 1, const Size2D &dilation = Size2D(1U, 1U),
                    const ICLTensor *output_multipliers = nullptr, const ICLTensor *output_shifts = nullptr);
+    /** Initialize the function's source, destination and parameters
+     *
+     * @param[in]  compile_context    The compile context to be used.
+     * @param[in]  input              Source tensor. Data type supported: QASYMM8/QASYMM8_SIGNED/FP32/FP16. Data layout supported: NHWC
+     * @param[in]  weights            Weights tensor. A 3D tensor with dimensions [IFM, N, M].
+     *                                Data type supported: Same as @p input or QASYMM8/QASYMM8_SIGNED/QSYMM8_PER_CHANNEL when @p input is QASYMM8.
+     * @param[in]  biases             Biases tensor. A 1D tensor with dimensions [IFM]. Must be nullptr if not needed.
+     *                                Data type supported: Same as @p input, S32 when input is QASYMM8/QASYMM8_SIGNED.
+     * @param[out] output             Destination tensor. Data type supported: Same as @p input.
+     * @param[in]  dwc_weights_info   Depthwise convolution layer weights info to retrieve the number of output elements processed by each thread
+     * @param[in]  dwc_info           Depthwise convolution layer info
+     * @param[in]  conv_info          Padding and stride information to use for the convolution.
+     * @param[in]  depth_multiplier   (Optional) Multiplier to apply to the input's depth in order to retrieve the output's depth. Defaults to 1.
+     * @param[in]  dilation           (Optional) Dilation, in elements, across x and y. Defaults to (1, 1).
+     * @param[in]  output_multipliers (Optional) Output multipliers tensor for quantized computations. In case of per-channel quantization,
+     *                                the number of multipliers must be equal to the number of filters (IFM). Supported data types: S32
+     * @param[in]  output_shifts      (Optional) Output shifts tensor for quantized computations. In case of per-channel quantization,
+     *                                the number of multipliers must be equal to the number of filters (IFM). Supported data types: S32
+     */
+    void configure(CLCompileContext &compile_context, const ICLTensor *input, const ICLTensor *weights, const ICLTensor *biases, ICLTensor *output, const DWCWeightsKernelInfo &dwc_weights_info,
+                   const DWCKernelInfo &dwc_info, const PadStrideInfo &conv_info, unsigned int depth_multiplier = 1, const Size2D &dilation = Size2D(1U, 1U),
+                   const ICLTensor *output_multipliers = nullptr, const ICLTensor *output_shifts = nullptr);
     /** Static function to check if given info will lead to a valid configuration of @ref CLDepthwiseConvolutionLayerNativeKernel
      *
      * @param[in] input              Source tensor info. Data type supported: QASYMM8/QASYMM8_SIGNED/FP32/FP16. Data layout supported: NHWC
diff --git a/arm_compute/core/CL/kernels/CLDepthwiseConvolutionLayerReshapeWeightsKernel.h b/arm_compute/core/CL/kernels/CLDepthwiseConvolutionLayerReshapeWeightsKernel.h
index 97225c7..e7fc6f8 100644
--- a/arm_compute/core/CL/kernels/CLDepthwiseConvolutionLayerReshapeWeightsKernel.h
+++ b/arm_compute/core/CL/kernels/CLDepthwiseConvolutionLayerReshapeWeightsKernel.h
@@ -52,6 +52,14 @@
      * @param[in]  info   Depthwise convolution information to reshape the input tensor.
      */
     void configure(const ICLTensor *input, ICLTensor *output, const DepthwiseConvolutionReshapeInfo &info);
+    /** Initialize the function's source and destination.
+     *
+     * @param[in]  compile_context The compile context to be used.
+     * @param[in]  input           The input tensor of dimension [IFM, W, H]. Data types supported: All. Data layouts supported: NHWC
+     * @param[out] output          The output tensor of dimension [W*H*C0, ceil(IFM/C0)]. C0 is the number of channels read by each thread. Data types supported: same as @p weights.
+     * @param[in]  info            Depthwise convolution information to reshape the input tensor.
+     */
+    void configure(CLCompileContext &compile_context, const ICLTensor *input, ICLTensor *output, const DepthwiseConvolutionReshapeInfo &info);
 
     /** Static function to check if given info will lead to a valid configuration of @ref CLDepthwiseConvolutionLayer3x3NHWCKernel
      *
diff --git a/arm_compute/core/CL/kernels/CLDequantizationLayerKernel.h b/arm_compute/core/CL/kernels/CLDequantizationLayerKernel.h
index 78b5c14..4cb1339 100644
--- a/arm_compute/core/CL/kernels/CLDequantizationLayerKernel.h
+++ b/arm_compute/core/CL/kernels/CLDequantizationLayerKernel.h
@@ -52,6 +52,13 @@
      * @param[out] output Destination tensor. Data types supported: F16/F32.
      */
     void configure(const ICLTensor *input, ICLTensor *output);
+    /** Set the input, output, min and max.
+     *
+     * @param[in]  compile_context The compile context to be used.
+     * @param[in]  input           Source tensor. Data types supported: QASYMM8/QASYMM8_SIGNED/QSYMM8_PER_CHANNEL/QSYMM8/QSYMM16.
+     * @param[out] output          Destination tensor. Data types supported: F16/F32.
+     */
+    void configure(CLCompileContext &compile_context, const ICLTensor *input, ICLTensor *output);
     /** Static function to check if given info will lead to a valid configuration of @ref CLDequantizationLayerKernel
      *
      * @param[in] input  Input tensor info. Data types supported: QASYMM8/QASYMM8_SIGNED/QSYMM8_PER_CHANNEL/QSYMM8/QSYMM16.
diff --git a/arm_compute/core/CL/kernels/CLDerivativeKernel.h b/arm_compute/core/CL/kernels/CLDerivativeKernel.h
index d6be5c2..5d5ad86 100644
--- a/arm_compute/core/CL/kernels/CLDerivativeKernel.h
+++ b/arm_compute/core/CL/kernels/CLDerivativeKernel.h
@@ -1,5 +1,5 @@
 /*
- * Copyright (c) 2016-2019 ARM Limited.
+ * Copyright (c) 2016-2020 ARM Limited.
  *
  * SPDX-License-Identifier: MIT
  *
@@ -56,6 +56,17 @@
      * @param[in]  border_undefined True if the border mode is undefined. False if it's replicate or constant.
      */
     void configure(const ICLTensor *input, ICLTensor *output_x, ICLTensor *output_y, bool border_undefined);
+    /** Initialise the kernel's sources, destination and border
+     *
+     * @note At least one of output_x or output_y must be set
+     *
+     * @param[in]  compile_context  The compile context to be used.
+     * @param[in]  input            Source tensor. Data types supported: U8.
+     * @param[out] output_x         (Optional) Destination tensor for the X gradient, Data types supported: S16.
+     * @param[out] output_y         (Optional) Destination tensor for the Y gradient, Data types supported: S16.
+     * @param[in]  border_undefined True if the border mode is undefined. False if it's replicate or constant.
+     */
+    void configure(CLCompileContext &compile_context, const ICLTensor *input, ICLTensor *output_x, ICLTensor *output_y, bool border_undefined);
 
     // Inherited methods overridden:
     void run(const Window &window, cl::CommandQueue &queue) override;
diff --git a/arm_compute/core/CL/kernels/CLDilateKernel.h b/arm_compute/core/CL/kernels/CLDilateKernel.h
index d131b34..9c41a84 100644
--- a/arm_compute/core/CL/kernels/CLDilateKernel.h
+++ b/arm_compute/core/CL/kernels/CLDilateKernel.h
@@ -1,5 +1,5 @@
 /*
- * Copyright (c) 2016-2019 ARM Limited.
+ * Copyright (c) 2016-2020 ARM Limited.
  *
  * SPDX-License-Identifier: MIT
  *
@@ -43,6 +43,14 @@
      * @param[in]  border_undefined True if the border mode is undefined. False if it's replicate or constant.
      */
     void configure(const ICLTensor *input, ICLTensor *output, bool border_undefined);
+    /**Initialise the kernel's input and output.
+     *
+     * @param[in]  compile_context  The compile context to be used.
+     * @param[in]  input            An input tensor. Data types supported: U8
+     * @param[out] output           The output tensor. Data types supported: U8.
+     * @param[in]  border_undefined True if the border mode is undefined. False if it's replicate or constant.
+     */
+    void configure(CLCompileContext &compile_context, const ICLTensor *input, ICLTensor *output, bool border_undefined);
 
     // Inherited methods overridden:
     BorderSize border_size() const override;
diff --git a/arm_compute/core/CL/kernels/CLDirectConvolutionLayerKernel.h b/arm_compute/core/CL/kernels/CLDirectConvolutionLayerKernel.h
index 5bf9a5d..f1409b6 100644
--- a/arm_compute/core/CL/kernels/CLDirectConvolutionLayerKernel.h
+++ b/arm_compute/core/CL/kernels/CLDirectConvolutionLayerKernel.h
@@ -68,6 +68,27 @@
      * @param[in]  conv_info Contains padding and stride information described in @ref PadStrideInfo.
      */
     void configure(const ICLTensor *input, const ICLTensor *weights, const ICLTensor *biases, ICLTensor *output, const PadStrideInfo &conv_info);
+    /** Set the input, weights, biases and output tensors.
+     *
+     * @note: DirectConvolution only works in the following configurations:
+     *        1x1 convolution with stride_x = 1/2/3, stride_y = 1/2/3
+     *        3x3 convolution with stride_x = 1/2, stride_y = 1/2
+     *        5x5 convolution with stride_x = 1/2, stride_y = 1/2
+     *        9x9 convolution with stride_x = 1/2, stride_y = 1/2, data_layout=NHWC
+     *
+     * @param[in]  compile_context The compile context to be used.
+     * @param[in]  input           The input tensor to convolve. 3 lower dimensions represent a single input [width, height, IFM],
+     *                             while every optional dimension from 4 and above represent a batch of inputs. Data types supported: QASYMM8_SIGNED/QASYMM8/F16/F32.
+     * @param[in]  weights         Weights tensor. Weights are 4D tensor with dimensions [kernel_x, kernel_y, IFM, OFM].
+     *                             The 3rd dimension must be the same as the input's volume 3rd dimension.
+     *                             Data type supported:Same as @p input.
+     * @param[in]  biases          Biases tensor. Biases are 1D tensor with dimension [OFM].
+     *                             Data type supported: Should match @p input data type, except for input of QASYMM8 and QASYMM8_SIGNED type where biases should be of S32 type
+     * @param[out] output          Output tensor.
+     *                             The 3rd dimensions must be equal to the 4th dimension of the @p kernels tensor. Data types supported: Same as @p input.
+     * @param[in]  conv_info       Contains padding and stride information described in @ref PadStrideInfo.
+     */
+    void configure(CLCompileContext &compile_context, const ICLTensor *input, const ICLTensor *weights, const ICLTensor *biases, ICLTensor *output, const PadStrideInfo &conv_info);
     /** Static function to check if given info will lead to a valid configuration of @ref CLDirectConvolutionLayerKernel
      *
      * @param[in] input     The input tensor to convolve. 3 lower dimensions represent a single input [width, height, IFM],
diff --git a/arm_compute/core/CL/kernels/CLElementWiseUnaryLayerKernel.h b/arm_compute/core/CL/kernels/CLElementWiseUnaryLayerKernel.h
index 0e4d2ec..1f76992 100644
--- a/arm_compute/core/CL/kernels/CLElementWiseUnaryLayerKernel.h
+++ b/arm_compute/core/CL/kernels/CLElementWiseUnaryLayerKernel.h
@@ -1,5 +1,5 @@
 /*
- * Copyright (c) 2018-2019 ARM Limited.
+ * Copyright (c) 2018-2020 ARM Limited.
  *
  * SPDX-License-Identifier: MIT
  *
@@ -43,6 +43,14 @@
      * @param[in]  op     Element wise unary operation to perform.
      */
     void configure(const ICLTensor *input, ICLTensor *output, const ElementWiseUnary &op);
+    /** Initialise the kernel's inputs, output.
+     *
+     * @param[in]  compile_context The compile context to be used.
+     * @param[in]  input           First tensor input. Data types supported: F16/F32.
+     * @param[out] output          Output tensor. Data types supported: Same as @p input.
+     * @param[in]  op              Element wise unary operation to perform.
+     */
+    void configure(CLCompileContext &compile_context, const ICLTensor *input, ICLTensor *output, const ElementWiseUnary &op);
     /** Static function to check if given info will lead to a valid configuration of @ref CLElementWiseUnaryLayerKernel
      *
      * @param[in] input  First tensor input info. Data types supported: F16/F32.
diff --git a/arm_compute/core/CL/kernels/CLElementwiseOperationKernel.h b/arm_compute/core/CL/kernels/CLElementwiseOperationKernel.h
index 85961f2..2f10601 100644
--- a/arm_compute/core/CL/kernels/CLElementwiseOperationKernel.h
+++ b/arm_compute/core/CL/kernels/CLElementwiseOperationKernel.h
@@ -96,6 +96,10 @@
      *
      */
     void configure_common(const ICLTensor *input1, const ICLTensor *input2, ICLTensor *output);
+    /** Commmon configure function for element-wise operators with no additional options (e.g., Div, Min, Max, SquaredDiff)
+     *
+     */
+    void configure_common(CLCompileContext &compile_context, const ICLTensor *input1, const ICLTensor *input2, ICLTensor *output);
 
     ActivationLayerInfo _act_info;
 
@@ -124,6 +128,18 @@
      * @param[in] act_info (Optional) Activation layer information in case of a fused activation.
      */
     void configure(ArithmeticOperation op, const ICLTensor *input1, const ICLTensor *input2, ICLTensor *output, const ConvertPolicy &policy, const ActivationLayerInfo &act_info = ActivationLayerInfo());
+    /** Static function to check if given info will lead to a valid configuration of @ref CLSaturatedArithmeticOperationKernel
+     *
+     * @param[in] compile_context The compile context to be used.
+     * @param[in] op              Arithmetic operation to be executed.
+     * @param[in] input1          First tensor input. Data types supported: U8/S8/QASYMM8/QASYMM8_SIGNED/U16/S16/QSYMM16/F16/U32/S32/F32.
+     * @param[in] input2          Second tensor input. Data types supported: Same as @p input1.
+     * @param[in] output          Output tensor. Data types supported: Same as @p input1.
+     * @param[in] policy          Policy to use to handle overflow.
+     * @param[in] act_info        (Optional) Activation layer information in case of a fused activation.
+     */
+    void configure(CLCompileContext &compile_context, ArithmeticOperation op, const ICLTensor *input1, const ICLTensor *input2, ICLTensor *output, const ConvertPolicy &policy,
+                   const ActivationLayerInfo &act_info = ActivationLayerInfo());
 
     /** Static function to check if given info will lead to a valid configuration of @ref CLSaturatedArithmeticOperationKernel
      *
@@ -169,6 +185,17 @@
      * @param[in] act_info (Optional) Activation layer information in case of a fused activation.
      */
     void configure(ArithmeticOperation op, const ICLTensor *input1, const ICLTensor *input2, ICLTensor *output, const ActivationLayerInfo &act_info = ActivationLayerInfo());
+    /** Static function to check if given info will lead to a valid configuration of @ref CLArithmeticOperationKernel
+     *
+     * @param[in] compile_context The compile context to be used.
+     * @param[in] op              Arithmetic operation to be executed.
+     * @param[in] input1          First tensor input. Data types supported: U8/S8/QASYMM8/QASYMM8_SIGNED/U16/S16/QSYMM16/F16/U32/S32/F32.
+     * @param[in] input2          Second tensor input. Data types supported: Same as @p input1.
+     * @param[in] output          Output tensor. Data types supported: Same as @p input1.
+     * @param[in] act_info        (Optional) Activation layer information in case of a fused activation.
+     */
+    void configure(CLCompileContext &compile_context, ArithmeticOperation op, const ICLTensor *input1, const ICLTensor *input2, ICLTensor *output,
+                   const ActivationLayerInfo &act_info = ActivationLayerInfo());
 
     /** Static function to check if given info will lead to a valid configuration of @ref CLArithmeticOperationKernel
      *
diff --git a/arm_compute/core/CL/kernels/CLErodeKernel.h b/arm_compute/core/CL/kernels/CLErodeKernel.h
index 4fcf70b..8ba6ff8 100644
--- a/arm_compute/core/CL/kernels/CLErodeKernel.h
+++ b/arm_compute/core/CL/kernels/CLErodeKernel.h
@@ -1,5 +1,5 @@
 /*
- * Copyright (c) 2016-2019 ARM Limited.
+ * Copyright (c) 2016-2020 ARM Limited.
  *
  * SPDX-License-Identifier: MIT
  *
@@ -43,6 +43,14 @@
      * @param[in]  border_undefined True if the border mode is undefined. False if it's replicate or constant.
      */
     void configure(const ICLTensor *input, ICLTensor *output, bool border_undefined);
+    /**Initialise the kernel's input and output.
+     *
+     * @param[in]  compile_context  The compile context to be used.
+     * @param[in]  input            An input tensor. Data types supported: U8
+     * @param[out] output           The output tensor. Data types supported: U8.
+     * @param[in]  border_undefined True if the border mode is undefined. False if it's replicate or constant.
+     */
+    void configure(CLCompileContext &compile_context, const ICLTensor *input, ICLTensor *output, bool border_undefined);
 
     // Inherited methods overridden:
     BorderSize border_size() const override;
diff --git a/arm_compute/core/CL/kernels/CLFFTDigitReverseKernel.h b/arm_compute/core/CL/kernels/CLFFTDigitReverseKernel.h
index 42eff76..eac03ff 100644
--- a/arm_compute/core/CL/kernels/CLFFTDigitReverseKernel.h
+++ b/arm_compute/core/CL/kernels/CLFFTDigitReverseKernel.h
@@ -1,5 +1,5 @@
 /*
- * Copyright (c) 2019 ARM Limited.
+ * Copyright (c) 2019-2020 ARM Limited.
  *
  * SPDX-License-Identifier: MIT
  *
@@ -57,6 +57,15 @@
      * @param[in]  config Kernel configuration.
      */
     void configure(const ICLTensor *input, ICLTensor *output, const ICLTensor *idx, const FFTDigitReverseKernelInfo &config);
+    /** Set the input and output tensors.
+     *
+     * @param[in]  compile_context The compile context to be used.
+     * @param[in]  input           Source tensor. Data types supported: F32.
+     * @param[out] output          Destination tensor. Data type supported: same as @p input
+     * @param[in]  idx             Digit reverse index tensor. Data type supported: U32
+     * @param[in]  config          Kernel configuration.
+     */
+    void configure(CLCompileContext &compile_context, const ICLTensor *input, ICLTensor *output, const ICLTensor *idx, const FFTDigitReverseKernelInfo &config);
     /** Static function to check if given info will lead to a valid configuration of @ref CLFFTDigitReverseKernel
      *
      * @param[in] input  Source tensor info. Data types supported: F32.
diff --git a/arm_compute/core/CL/kernels/CLFFTRadixStageKernel.h b/arm_compute/core/CL/kernels/CLFFTRadixStageKernel.h
index b88ab1a..85bf4cc 100644
--- a/arm_compute/core/CL/kernels/CLFFTRadixStageKernel.h
+++ b/arm_compute/core/CL/kernels/CLFFTRadixStageKernel.h
@@ -1,5 +1,5 @@
 /*
- * Copyright (c) 2019 ARM Limited.
+ * Copyright (c) 2019-2020 ARM Limited.
  *
  * SPDX-License-Identifier: MIT
  *
@@ -60,6 +60,16 @@
      * @param[in]     config FFT descriptor metadata.
      */
     void configure(ICLTensor *input, ICLTensor *output, const FFTRadixStageKernelInfo &config);
+    /** Set the input and output tensors.
+     *
+     * @note If the output tensor is nullptr, the FFT will be performed in-place
+     *
+     * @param[in]     compile_context The compile context to be used.
+     * @param[in,out] input           Source tensor. Data types supported: F32.
+     * @param[out]    output          Destination tensor. Can be nullptr. Data type supported: same as @p input
+     * @param[in]     config          FFT descriptor metadata.
+     */
+    void configure(CLCompileContext &compile_context, ICLTensor *input, ICLTensor *output, const FFTRadixStageKernelInfo &config);
     /** Static function to check if given info will lead to a valid configuration of @ref CLFFTRadixStageKernel
      *
      * @param[in] input  Source tensor info. Data types supported: F32.
diff --git a/arm_compute/core/CL/kernels/CLFFTScaleKernel.h b/arm_compute/core/CL/kernels/CLFFTScaleKernel.h
index 3a069fe..cd4fe58 100644
--- a/arm_compute/core/CL/kernels/CLFFTScaleKernel.h
+++ b/arm_compute/core/CL/kernels/CLFFTScaleKernel.h
@@ -1,5 +1,5 @@
 /*
- * Copyright (c) 2019 ARM Limited.
+ * Copyright (c) 2019-2020 ARM Limited.
  *
  * SPDX-License-Identifier: MIT
  *
@@ -56,6 +56,14 @@
      * @param[in]     config Kernel configuration
      */
     void configure(ICLTensor *input, ICLTensor *output, const FFTScaleKernelInfo &config);
+    /** Set the input and output tensors.
+     *
+     * @param[in]     compile_context The compile context to be used.
+     * @param[in,out] input           Source tensor. Data types supported: F32.
+     * @param[out]    output          Destination tensor. Data type supported: same as @p input
+     * @param[in]     config          Kernel configuration
+     */
+    void configure(CLCompileContext &compile_context, ICLTensor *input, ICLTensor *output, const FFTScaleKernelInfo &config);
     /** Static function to check if given info will lead to a valid configuration of @ref CLFFTScaleKernel
      *
      * @param[in] input  Source tensor info. Data types supported: F32.
diff --git a/arm_compute/core/CL/kernels/CLFastCornersKernel.h b/arm_compute/core/CL/kernels/CLFastCornersKernel.h
index 3cca39e..2a61020 100644
--- a/arm_compute/core/CL/kernels/CLFastCornersKernel.h
+++ b/arm_compute/core/CL/kernels/CLFastCornersKernel.h
@@ -1,5 +1,5 @@
 /*
- * Copyright (c) 2016-2019 ARM Limited.
+ * Copyright (c) 2016-2020 ARM Limited.
  *
  * SPDX-License-Identifier: MIT
  *
@@ -66,6 +66,16 @@
      * @param[in]  border_mode         Strategy to use for borders.
      */
     void configure(const ICLImage *input, ICLImage *output, float threshold, bool non_max_suppression, BorderMode border_mode);
+    /** Initialise the kernel.
+     *
+     * @param[in]  compile_context     The compile context to be used.
+     * @param[in]  input               Source image. Data types supported: U8.
+     * @param[out] output              Output image. Data types supported: U8.
+     * @param[in]  threshold           Threshold on difference between intensity of the central pixel and pixels on Bresenham's circle of radius 3.
+     * @param[in]  non_max_suppression True if non-maxima suppresion is applied, false otherwise.
+     * @param[in]  border_mode         Strategy to use for borders.
+     */
+    void configure(CLCompileContext &compile_context, const ICLImage *input, ICLImage *output, float threshold, bool non_max_suppression, BorderMode border_mode);
 
     // Inherited methods overridden
     void run(const Window &window, cl::CommandQueue &queue) override;
@@ -101,6 +111,15 @@
      * @param[out] num_buffers   Number of keypoints to store the results.
      */
     void configure(const ICLImage *input, bool update_number, ICLKeyPointArray *corners, cl::Buffer *num_buffers);
+    /** Initialise the kernel.
+     *
+     * @param[in]  compile_context The compile context to be used.
+     * @param[in]  input           Source image. Data types supported: U8.
+     * @param[in]  update_number   Flag to indicate whether we need to update the number of corners
+     * @param[out] corners         Array of keypoints to store the results.
+     * @param[out] num_buffers     Number of keypoints to store the results.
+     */
+    void configure(CLCompileContext &compile_context, const ICLImage *input, bool update_number, ICLKeyPointArray *corners, cl::Buffer *num_buffers);
 
     // Inherited methods overridden:
     void run(const Window &window, cl::CommandQueue &queue) override;
diff --git a/arm_compute/core/CL/kernels/CLFillBorderKernel.h b/arm_compute/core/CL/kernels/CLFillBorderKernel.h
index 36f54c5..226b611 100644
--- a/arm_compute/core/CL/kernels/CLFillBorderKernel.h
+++ b/arm_compute/core/CL/kernels/CLFillBorderKernel.h
@@ -57,6 +57,15 @@
      * @param[in]     constant_border_value (Optional) Constant value to use for borders if border_mode is set to CONSTANT.
      */
     void configure(ICLTensor *tensor, BorderSize border_size, BorderMode border_mode, const PixelValue &constant_border_value = PixelValue());
+    /** Initialise the kernel's input, output and border mode.
+     *
+     * @param[in]     compile_context       The compile context to be used.
+     * @param[in,out] tensor                Tensor to process Data types supported: U8/QASYMM8/S8/QASYMM8_SIGNED/U16/S16/U32/S32/F16/F32.
+     * @param[in]     border_size           Size of the border to fill in elements.
+     * @param[in]     border_mode           Border mode to use for the convolution.
+     * @param[in]     constant_border_value (Optional) Constant value to use for borders if border_mode is set to CONSTANT.
+     */
+    void configure(CLCompileContext &compile_context, ICLTensor *tensor, BorderSize border_size, BorderMode border_mode, const PixelValue &constant_border_value = PixelValue());
 
     /** Function to set the constant value on fill border kernel depending on type.
      *
diff --git a/arm_compute/core/CL/kernels/CLFlattenLayerKernel.h b/arm_compute/core/CL/kernels/CLFlattenLayerKernel.h
index 1b7fdcc..b795e03 100644
--- a/arm_compute/core/CL/kernels/CLFlattenLayerKernel.h
+++ b/arm_compute/core/CL/kernels/CLFlattenLayerKernel.h
@@ -52,6 +52,15 @@
      *                    w = width input tensor, h = height input tensor and d = depth input tensor. Data type supported: same as @p input
      */
     void configure(const ICLTensor *input, ICLTensor *output);
+    /** Set the input and output of the kernel.
+     *
+     * @param[in]  compile_context The compile context to be used.
+     * @param[in]  input           First input tensor to flatten with at least 3 dimensions.
+     *                             The dimensions above the third will be interpreted as batches. Data types supported: All.
+     * @param[out] output          Output tensor with shape [w*h*d, input_batches] where:
+     *                    w = width input tensor, h = height input tensor and d = depth input tensor. Data type supported: same as @p input
+     */
+    void configure(CLCompileContext &compile_context, const ICLTensor *input, ICLTensor *output);
     /** Static function to check if given info will lead to a valid configuration of @ref CLFlattenLayerKernel
      *
      * @param[in]  input  First input tensor to flatten with at least 3 dimensions.
diff --git a/arm_compute/core/CL/kernels/CLFuseBatchNormalizationKernel.h b/arm_compute/core/CL/kernels/CLFuseBatchNormalizationKernel.h
index aa60376..2d62a57 100644
--- a/arm_compute/core/CL/kernels/CLFuseBatchNormalizationKernel.h
+++ b/arm_compute/core/CL/kernels/CLFuseBatchNormalizationKernel.h
@@ -1,5 +1,5 @@
 /*
- * Copyright (c) 2018-2019 ARM Limited.
+ * Copyright (c) 2018-2020 ARM Limited.
  *
  * SPDX-License-Identifier: MIT
  *
@@ -65,6 +65,25 @@
     void configure(const ICLTensor *input_weights, const ICLTensor *bn_mean, const ICLTensor *bn_var, ICLTensor *fused_weights, ICLTensor *fused_bias,
                    const ICLTensor *input_bias = nullptr, const ICLTensor *bn_beta = nullptr, const ICLTensor *bn_gamma = nullptr,
                    float epsilon = 0.001f, FuseBatchNormalizationType fbn_type = FuseBatchNormalizationType::CONVOLUTION);
+    /** Set the source, destination of the kernel
+     *
+     * @param[in]  compile_context The compile context to be used.
+     * @param[in]  input_weights   Input weights tensor for convolution or depthwise convolution layer. Data type supported: F16/F32. Data layout supported: NCHW, NHWC
+     * @param[in]  bn_mean         Batch normalization layer mean tensor. Same as @p input_weights
+     * @param[in]  bn_var          Batch normalization layer variance tensor. Same as @p input_weights
+     * @param[out] fused_weights   Output fused weights tensor. It can be a nullptr in case of in-place computation. Same as @p input_weights
+     * @param[out] fused_bias      Output fused bias tensor. It can be a nullptr in case of in-place computation and input_bias != nullptr. Same as @p input_weights
+     * @param[in]  input_bias      (Optional) Input bias tensor for convolution or depthwise convolution layer. It can be a nullptr in case the bias tensor is not required. Same as @p input_weights
+     * @param[in]  bn_beta         (Optional) Batch normalization layer beta tensor. It can be a nullptr in case the beta tensor is not required. Same as @p input_weights
+     *                             @note if nullptr, bn_beta is set to 0.0
+     * @param[in]  bn_gamma        (Optional) Batch normalization layer gamma tensor. It can be a nullptr in case the gamma tensor is not required. Same as @p input_weights
+     *                             @note if nullptr, bn_gamma is set to 1.0
+     * @param[in]  epsilon         (Optional) Batch normalization layer epsilon parameter. Defaults to 0.001f.
+     * @param[in]  fbn_type        (Optional) Fused batch normalization type. Defaults to CONVOLUTION.
+     */
+    void configure(CLCompileContext &compile_context, const ICLTensor *input_weights, const ICLTensor *bn_mean, const ICLTensor *bn_var, ICLTensor *fused_weights, ICLTensor *fused_bias,
+                   const ICLTensor *input_bias = nullptr, const ICLTensor *bn_beta = nullptr, const ICLTensor *bn_gamma = nullptr,
+                   float epsilon = 0.001f, FuseBatchNormalizationType fbn_type = FuseBatchNormalizationType::CONVOLUTION);
     /** Static function to check if given info will lead to a valid configuration of @ref CLFuseBatchNormalizationKernel
      *
      * @param[in] input_weights Input weights tensor info for convolution or depthwise convolution layer. Data type supported: F16/F32. Data layout supported: NCHW, NHWC
diff --git a/arm_compute/core/CL/kernels/CLGEMMLowpMatrixMultiplyKernel.h b/arm_compute/core/CL/kernels/CLGEMMLowpMatrixMultiplyKernel.h
index a8853d4..e926f5e 100644
--- a/arm_compute/core/CL/kernels/CLGEMMLowpMatrixMultiplyKernel.h
+++ b/arm_compute/core/CL/kernels/CLGEMMLowpMatrixMultiplyKernel.h
@@ -1,5 +1,5 @@
 /*
- * Copyright (c) 2017-2019 ARM Limited.
+ * Copyright (c) 2017-2020 ARM Limited.
  *
  * SPDX-License-Identifier: MIT
  *
@@ -64,6 +64,17 @@
      * @param[in]  gemm_info (Optional) GEMM information used to retrieve the original dimensions of the input matrices
      */
     void configure(const ICLTensor *input0, const ICLTensor *input1, ICLTensor *output, const GEMMReshapeInfo &gemm_info = GEMMReshapeInfo());
+    /** Initialise the kernel's input and output.
+     *
+     * @note This kernel should be used ONLY for Midgard architectures
+     *
+     * @param[in]  compile_context The compile context to be used.
+     * @param[in]  input0          Input tensor containing the LHS matrix. Data type supported: QASYMM8
+     * @param[in]  input1          Input tensor containing the RHS matrix. Data type supported: same as @p input0
+     * @param[out] output          Output tensor to store the result of matrix multiplication. Data type supported: S32
+     * @param[in]  gemm_info       (Optional) GEMM information used to retrieve the original dimensions of the input matrices
+     */
+    void configure(CLCompileContext &compile_context, const ICLTensor *input0, const ICLTensor *input1, ICLTensor *output, const GEMMReshapeInfo &gemm_info = GEMMReshapeInfo());
     /** Static function to check if given info will lead to a valid configuration of @ref CLGEMMLowpMatrixMultiplyKernel
      *
      * @param[in] input0    Input tensor containing the LHS matrix. Data type supported: QASYMM8
diff --git a/arm_compute/core/CL/kernels/CLGEMMLowpMatrixMultiplyNativeKernel.h b/arm_compute/core/CL/kernels/CLGEMMLowpMatrixMultiplyNativeKernel.h
index e1191f2..d100efd 100644
--- a/arm_compute/core/CL/kernels/CLGEMMLowpMatrixMultiplyNativeKernel.h
+++ b/arm_compute/core/CL/kernels/CLGEMMLowpMatrixMultiplyNativeKernel.h
@@ -58,6 +58,22 @@
      * @param[in]  gemm_info GEMM information used to retrieve the original dimensions of the input matrices
      */
     void configure(const ICLTensor *input0, const ICLTensor *input1, ICLTensor *output, const GEMMLHSMatrixInfo &lhs_info, const GEMMRHSMatrixInfo &rhs_info, const GEMMReshapeInfo &gemm_info);
+    /** Initialise the kernel's input and output.
+     *
+     * @param[in]  compile_context The compile context to be used.
+     * @param[in]  input0          Input tensor containing the LHS matrix. Data type supported: QASYMM8/QASYMM8_SIGNED
+     * @param[in]  input1          Input tensor containing the RHS matrix. Data type supported: same as @p input0
+     * @param[out] output          Output tensor to store the result of matrix multiplication. Data type supported: S32
+     * @param[in]  lhs_info        LHS matrix information used to retrieve the number of rows to be processed by each thread
+     *                             lhs_info.m0: 2,3,4,5,6,7,8
+     *                             lhs_info.k0: 2,3,4,8,16
+     * @param[in]  rhs_info        RHS matrix information used to retrieve the number of columns to be processed by each thread
+     *                             rhs_info.n0: 2,3,4,8,16
+     *                             rhs_info.k0: same as lhs_info.k0
+     * @param[in]  gemm_info       GEMM information used to retrieve the original dimensions of the input matrices
+     */
+    void configure(CLCompileContext &compile_context, const ICLTensor *input0, const ICLTensor *input1, ICLTensor *output, const GEMMLHSMatrixInfo &lhs_info, const GEMMRHSMatrixInfo &rhs_info,
+                   const GEMMReshapeInfo &gemm_info);
     /** Static function to check if given info will lead to a valid configuration of @ref CLGEMMLowpMatrixMultiplyNativeKernel
      *
      * @param[in] input0    Input tensor info for the LHS matrix. Data type supported: QASYMM8/QASYMM8_SIGNED
diff --git a/arm_compute/core/CL/kernels/CLGEMMLowpMatrixMultiplyReshapedKernel.h b/arm_compute/core/CL/kernels/CLGEMMLowpMatrixMultiplyReshapedKernel.h
index 64a9812..9e3b198 100644
--- a/arm_compute/core/CL/kernels/CLGEMMLowpMatrixMultiplyReshapedKernel.h
+++ b/arm_compute/core/CL/kernels/CLGEMMLowpMatrixMultiplyReshapedKernel.h
@@ -65,6 +65,26 @@
      * @note lhs_info.k0 must be equal to rhs_info.k0
      */
     void configure(const ICLTensor *input0, const ICLTensor *input1, ICLTensor *output, const GEMMLHSMatrixInfo &lhs_info, const GEMMRHSMatrixInfo &rhs_info, const GEMMReshapeInfo &gemm_info);
+    /** Initialise the kernel's input and output.
+     *
+     * @param[in]  compile_context The compile context to be used.
+     * @param[in]  input0          Input tensor containing the LHS reshaped matrix. Data type supported: QASYMM8/QASYMM8_SIGNED. The number of dimensions for the LHS matrix must be less or equal than 4.
+     * @param[in]  input1          Input tensor containing the RHS reshaped matrix. Data type supported: same as @p input0. The number of dimensions for the RHS matrix must be less or equal than 3.
+     * @param[out] output          Output tensor to store the result of matrix multiplication. Data type supported: S32
+     * @param[in]  lhs_info        LHS matrix information used for reshaping the input0 tensor.  Only the following values are supported:
+     *                             lhs_info.m0: 2,3,4,5,6,7,8
+     *                             lhs_info.k0: 2,3,4,8,16
+     *                             lhs_info.transpose: false
+     * @param[in]  rhs_info        RHS matrix information used for reshaping the input1 tensor.  Only the following values are supported:
+     *                             rhs_info.n0: 2,3,4,8,16
+     *                             rhs_info.k0: same as lhs_info.k0
+     *                             rhs_info.transpose: true
+     * @param[in]  gemm_info       GEMM information used to retrieve the original dimensions of the input matrices
+     *
+     * @note lhs_info.k0 must be equal to rhs_info.k0
+     */
+    void configure(CLCompileContext &compile_context, const ICLTensor *input0, const ICLTensor *input1, ICLTensor *output, const GEMMLHSMatrixInfo &lhs_info, const GEMMRHSMatrixInfo &rhs_info,
+                   const GEMMReshapeInfo &gemm_info);
     /** Static function to check if given info will lead to a valid configuration of @ref CLGEMMLowpMatrixMultiplyReshapedKernel
      *
      * @param[in] input0    Input tensor info containing the LHS reshaped matrix. Data type supported: QASYMM8/QASYMM8_SIGNED. The number of dimensions for the LHS matrix must be less or equal than 4.
diff --git a/arm_compute/core/CL/kernels/CLGEMMLowpMatrixMultiplyReshapedOnlyRHSKernel.h b/arm_compute/core/CL/kernels/CLGEMMLowpMatrixMultiplyReshapedOnlyRHSKernel.h
index 7845d24..cc3c5f5 100644
--- a/arm_compute/core/CL/kernels/CLGEMMLowpMatrixMultiplyReshapedOnlyRHSKernel.h
+++ b/arm_compute/core/CL/kernels/CLGEMMLowpMatrixMultiplyReshapedOnlyRHSKernel.h
@@ -75,6 +75,33 @@
      */
     void configure(const ICLTensor *input0, const ICLTensor *input1, ICLTensor *output, const GEMMKernelInfo &gemm_info, const ICLTensor *vector_sum_col = nullptr,
                    const ICLTensor *vector_sum_row = nullptr, const ICLTensor *bias = nullptr, const ICLTensor *output_multipliers = nullptr, const ICLTensor *output_shifts = nullptr);
+    /** Initialise the kernel's input and output.
+     *
+     * @param[in]  compile_context    The compile context to be used.
+     * @param[in]  input0             Input tensor containing the LHS matrix. Data type supported: QASYMM8/QASYMM8_SIGNED
+     * @param[in]  input1             Input tensor containing the RHS reshaped matrix. Data type supported: same as @p input0
+     * @param[out] output             Output tensor. Data type supported: QASYMM8/QASYMM8_SIGNED/S32.
+     * @param[in]  gemm_info          GEMM information used to retrieve the original dimensions of the input matrices, output stage information and RHS/LHS info.
+     *                                Only the following values are supported for LHS info:
+     *                                lhs_info.m0: 2,3,4,5,6,7,8
+     *                                lhs_info.k0: 2,3,4,8,16
+     *                                Only the following values are supported for RHS info:
+     *                                rhs_info.n0: 2,3,4,8,16
+     *                                rhs_info.k0: same as lhs_info.k0
+     *                                rhs_info.transpose: true
+     * @param[in]  vector_sum_col     (Optional) Input row-vector of sums of all the entries in each column of matrix B.
+     *                                Note: vector_sum_col can be a nullptr in case a_offset = 0. Data type supported: S32
+     * @param[in]  vector_sum_row     (Optional) Input row-vector of sums of all the entries in each row of matrix A.
+     *                                Note: vector_sum_row can be a nullptr in case b_offset = 0. Data type supported: S32
+     * @param[in]  bias               (Optional) Biases tensor. Only shared biases supported and it can be a nullptr if the addition of biases is not required.
+     *                                Biases are 1D tensor with dimensions [OFM]. Data type supported: S32.
+     * @param[in]  output_multipliers (Optional) Output multipliers tensor. In case of per-channel quantization, the number of multipliers must be equal to the number of filters (OFM).
+     *                                Supported data types: S32.
+     * @param[in]  output_shifts      (Optional) Output shifts tensor. In case of per-channel quantization, the number of multipliers must be equal to the number of filters (OFM).
+     *                                Supported data types: S32.
+     */
+    void configure(CLCompileContext &compile_context, const ICLTensor *input0, const ICLTensor *input1, ICLTensor *output, const GEMMKernelInfo &gemm_info, const ICLTensor *vector_sum_col = nullptr,
+                   const ICLTensor *vector_sum_row = nullptr, const ICLTensor *bias = nullptr, const ICLTensor *output_multipliers = nullptr, const ICLTensor *output_shifts = nullptr);
     /** Static function to check if given info will lead to a valid configuration of @ref CLGEMMLowpMatrixMultiplyReshapedOnlyRHSKernel
      *
      * @param[in] input0             Input tensor info for the LHS matrix. Data type supported: QASYMM8/QASYMM8_SIGNED
diff --git a/arm_compute/core/CL/kernels/CLGEMMLowpOffsetContributionKernel.h b/arm_compute/core/CL/kernels/CLGEMMLowpOffsetContributionKernel.h
index f029104..d7266b2 100644
--- a/arm_compute/core/CL/kernels/CLGEMMLowpOffsetContributionKernel.h
+++ b/arm_compute/core/CL/kernels/CLGEMMLowpOffsetContributionKernel.h
@@ -1,5 +1,5 @@
 /*
- * Copyright (c) 2017-2019 ARM Limited.
+ * Copyright (c) 2017-2020 ARM Limited.
  *
  * SPDX-License-Identifier: MIT
  *
@@ -70,6 +70,22 @@
      * @param[in]      b_offset       Offset to be added to each element of the matrix B.
      */
     void configure(ICLTensor *mm_result, const ICLTensor *vector_sum_col, const ICLTensor *vector_sum_row, const ICLTensor *bias, int32_t k, int32_t a_offset, int32_t b_offset);
+    /** Initialise the kernel's input and output.
+     *
+     * @param[in]      compile_context The compile context to be used.
+     * @param[in, out] mm_result       Input tensor containing the result of @ref CLGEMMLowpMatrixMultiplyKernel. Data type supported: S32
+     * @param[in]      vector_sum_col  Input row-vector of sums of all the entries in each column of matrix B.
+     *                                 Note: vector_sum_col can be a nullptr in case a_offset = 0. Data type supported: same as @p mm_result
+     * @param[in]      vector_sum_row  Input row-vector of sums of all the entries in each row of matrix A.
+     *                                 Note: vector_sum_row can be a nullptr in case b_offset = 0. Data type supported: same as @p mm_result
+     * @param[in]      bias            Biases tensor. Only shared biases supported and it can be a nullptr if the addition of biases is not required.
+     *                                 Biases are 1D tensor with dimensions [OFM]. Data type supported: Same as @p input.
+     * @param[in]      k               Number of matrix A columns or Matrix B rows
+     * @param[in]      a_offset        Offset to be added to each element of the matrix A.
+     * @param[in]      b_offset        Offset to be added to each element of the matrix B.
+     */
+    void configure(CLCompileContext &compile_context, ICLTensor *mm_result, const ICLTensor *vector_sum_col, const ICLTensor *vector_sum_row, const ICLTensor *bias, int32_t k, int32_t a_offset,
+                   int32_t b_offset);
     /** Static function to check if given info will lead to a valid configuration of @ref CLGEMMLowpOffsetContributionKernel
      *
      * @param[in] mm_result      Input tensor containing the result of @ref CLGEMMLowpOffsetContributionKernel. Data type supported: S32
diff --git a/arm_compute/core/CL/kernels/CLGEMMLowpOffsetContributionOutputStageKernel.h b/arm_compute/core/CL/kernels/CLGEMMLowpOffsetContributionOutputStageKernel.h
index 4094bc6..02ed20e 100644
--- a/arm_compute/core/CL/kernels/CLGEMMLowpOffsetContributionOutputStageKernel.h
+++ b/arm_compute/core/CL/kernels/CLGEMMLowpOffsetContributionOutputStageKernel.h
@@ -71,6 +71,29 @@
      */
     void configure(const ICLTensor *mm_result, const ICLTensor *vector_sum_col, const ICLTensor *vector_sum_row, const ICLTensor *bias, ICLTensor *output, int32_t k, int32_t a_offset, int32_t b_offset,
                    const GEMMLowpOutputStageInfo &output_stage, const ICLTensor *output_multipliers, const ICLTensor *output_shifts);
+    /** Initialise the kernel's input and output.
+     *
+     * @param[in]  compile_context    The compile context to be used.
+     * @param[in]  mm_result          Input tensor containing the result of @ref CLGEMMLowpMatrixMultiplyKernel. Data type supported: S32
+     * @param[in]  vector_sum_col     Input row-vector of sums of all the entries in each column of matrix B.
+     *                                Note: vector_sum_col can be a nullptr in case a_offset = 0. Data type supported: same as @p mm_result
+     * @param[in]  vector_sum_row     Input row-vector of sums of all the entries in each row of matrix A.
+     *                                Note: vector_sum_row can be a nullptr in case b_offset = 0. Data type supported: same as @p mm_result
+     * @param[in]  bias               Biases tensor. Only shared biases supported and it can be a nullptr if the addition of biases is not required.
+     *                                Biases are 1D tensor with dimensions [OFM]. Data type supported: Same as @p input.
+     * @param[out] output             Output tensor. Data type supported: QASYMM8/QASYMM8_SIGNED.
+     * @param[in]  k                  Number of matrix A columns or Matrix B rows
+     * @param[in]  a_offset           Offset to be added to each element of the matrix A.
+     * @param[in]  b_offset           Offset to be added to each element of the matrix B.
+     * @param[in]  output_stage       GEMMLowp output stage info
+     * @param[in]  output_multipliers Output multipliers tensor. In case of per-channel quantization, the number of multipliers must be equal to the number of filters (OFM).
+     *                                Supported data types: S32
+     * @param[in]  output_shifts      Output shifts tensor. In case of per-channel quantization, the number of multipliers must be equal to the number of filters (OFM).
+     *                                Supported data types: S32
+     */
+    void configure(CLCompileContext &compile_context, const ICLTensor *mm_result, const ICLTensor *vector_sum_col, const ICLTensor *vector_sum_row, const ICLTensor *bias, ICLTensor *output, int32_t k,
+                   int32_t a_offset, int32_t b_offset,
+                   const GEMMLowpOutputStageInfo &output_stage, const ICLTensor *output_multipliers, const ICLTensor *output_shifts);
     /** Static function to check if given info will lead to a valid configuration of @ref CLGEMMLowpOffsetContributionKernel
      *
      * @param[in] mm_result          Input tensor containing the result of @ref CLGEMMLowpOffsetContributionKernel. Data type supported: S32
diff --git a/arm_compute/core/CL/kernels/CLGEMMLowpQuantizeDownInt32ScaleByFloatKernel.h b/arm_compute/core/CL/kernels/CLGEMMLowpQuantizeDownInt32ScaleByFloatKernel.h
index 439f569..0b5b22c 100644
--- a/arm_compute/core/CL/kernels/CLGEMMLowpQuantizeDownInt32ScaleByFloatKernel.h
+++ b/arm_compute/core/CL/kernels/CLGEMMLowpQuantizeDownInt32ScaleByFloatKernel.h
@@ -67,6 +67,16 @@
      * @param[in]  info   Output stage info. Used to pass the quantized output data type
      */
     void configure(const ICLTensor *input, const ICLTensor *bias, ICLTensor *output, const GEMMLowpOutputStageInfo *info);
+    /** Initialise the kernel's input and output.
+     *
+     * @param[in]  compile_context The compile context to be used.
+     * @param[in]  input           Input tensor. Data type supported: S32
+     * @param[in]  bias            Biases tensor. Only shared biases supported and it can be a nullptr if the biases addition is not required.
+     *                             Biases are 1D tensor with dimensions [OFM]. Data type supported: Same as @p input.
+     * @param[out] output          Output tensor. Data type supported: Data type supported: QASYMM8/QASYMM8_SIGNED
+     * @param[in]  info            Output stage info. Used to pass the quantized output data type
+     */
+    void configure(CLCompileContext &compile_context, const ICLTensor *input, const ICLTensor *bias, ICLTensor *output, const GEMMLowpOutputStageInfo *info);
     /** Static function to check if given info will lead to a valid configuration of @ref CLGEMMLowpQuantizeDownInt32ScaleByFloatKernel
      *
      * @param[in] input  Input tensor. Data type supported: S32
diff --git a/arm_compute/core/CL/kernels/CLGEMMLowpQuantizeDownInt32ScaleKernel.h b/arm_compute/core/CL/kernels/CLGEMMLowpQuantizeDownInt32ScaleKernel.h
index 3378359..0d7d1c3 100644
--- a/arm_compute/core/CL/kernels/CLGEMMLowpQuantizeDownInt32ScaleKernel.h
+++ b/arm_compute/core/CL/kernels/CLGEMMLowpQuantizeDownInt32ScaleKernel.h
@@ -67,6 +67,16 @@
      * @param[in]  output_stage GEMMLowp output stage metadata.
      */
     void configure(const ICLTensor *input, const ICLTensor *bias, ICLTensor *output, const GEMMLowpOutputStageInfo *output_stage);
+    /** Initialise the kernel's input and output.
+     *
+     * @param[in]  compile_context The compile context to be used.
+     * @param[in]  input           Input tensor. Data type supported: S32
+     * @param[in]  bias            Biases tensor. Only shared biases supported and it can be a nullptr if the biases addition is not required.
+     *                             Biases are 1D tensor with dimensions [OFM]. Data type supported: Same as @p input.
+     * @param[out] output          Output tensor. Data type supported: Data type supported: QASYMM8/QASYMM8_SIGNED
+     * @param[in]  output_stage    GEMMLowp output stage metadata.
+     */
+    void configure(CLCompileContext &compile_context, const ICLTensor *input, const ICLTensor *bias, ICLTensor *output, const GEMMLowpOutputStageInfo *output_stage);
     /** Static function to check if given info will lead to a valid configuration of @ref CLGEMMLowpQuantizeDownInt32ScaleKernel
      *
      * @param[in] input        Input tensor. Data type supported: S32
diff --git a/arm_compute/core/CL/kernels/CLGEMMLowpQuantizeDownInt32ToInt16ScaleByFixedPointKernel.h b/arm_compute/core/CL/kernels/CLGEMMLowpQuantizeDownInt32ToInt16ScaleByFixedPointKernel.h
index 72ca4c5..2845d92 100644
--- a/arm_compute/core/CL/kernels/CLGEMMLowpQuantizeDownInt32ToInt16ScaleByFixedPointKernel.h
+++ b/arm_compute/core/CL/kernels/CLGEMMLowpQuantizeDownInt32ToInt16ScaleByFixedPointKernel.h
@@ -1,5 +1,5 @@
 /*
- * Copyright (c) 2019 ARM Limited.
+ * Copyright (c) 2019-2020 ARM Limited.
  *
  * SPDX-License-Identifier: MIT
  *
@@ -68,6 +68,20 @@
      *                                          Along with @p min, this value can be used to implement "rectified linear unit" activation functions. Defaults to 0.
      */
     void configure(const ICLTensor *input, const ICLTensor *bias, ICLTensor *output, int result_fixedpoint_multiplier, int result_shift, int min = 0, int max = 0);
+    /** Initialise the kernel's input and output.
+     *
+     * @param[in]  compile_context              The compile context to be used.
+     * @param[in]  input                        Input tensor. Data type supported: S32
+     * @param[in]  bias                         Biases tensor. Only shared biases supported and it can be a nullptr if the biases addition is not required.
+     *                                          Biases are 1D tensor with dimensions [OFM]. Data type supported: Same as @p input.
+     * @param[out] output                       Output tensor. Data type supported: Data type supported: QSYMM16
+     * @param[in]  result_fixedpoint_multiplier Fixed point value to be multiplied to each element of the input matrix when once the result_offset has been add
+     * @param[in]  result_shift                 Integer value used to round to nearest division by a power-of-two the result after the fixed point multiplication
+     * @param[in]  min                          (Optional) Min value used to saturate down the output result before converting back to QSYMM16. Defaults to 0.
+     * @param[in]  max                          (Optional) Max value used to saturate up the output result before converting back to QSYMM16.
+     *                                          Along with @p min, this value can be used to implement "rectified linear unit" activation functions. Defaults to 0.
+     */
+    void configure(CLCompileContext &compile_context, const ICLTensor *input, const ICLTensor *bias, ICLTensor *output, int result_fixedpoint_multiplier, int result_shift, int min = 0, int max = 0);
     /** Static function to check if given info will lead to a valid configuration of @ref CLGEMMLowpQuantizeDownInt32ToInt16ScaleByFixedPointKernel
      *
      * @param[in] input  Input tensor info. Data type supported: S32
diff --git a/arm_compute/core/CL/kernels/CLGEMMLowpQuantizeDownInt32ToInt8ScaleByFixedPointKernel.h b/arm_compute/core/CL/kernels/CLGEMMLowpQuantizeDownInt32ToInt8ScaleByFixedPointKernel.h
index 22ac8fa..a768b6f 100644
--- a/arm_compute/core/CL/kernels/CLGEMMLowpQuantizeDownInt32ToInt8ScaleByFixedPointKernel.h
+++ b/arm_compute/core/CL/kernels/CLGEMMLowpQuantizeDownInt32ToInt8ScaleByFixedPointKernel.h
@@ -1,5 +1,5 @@
 /*
- * Copyright (c) 2019 ARM Limited.
+ * Copyright (c) 2019-2020 ARM Limited.
  *
  * SPDX-License-Identifier: MIT
  *
@@ -70,6 +70,22 @@
      */
     void configure(const ICLTensor *input, const ICLTensor *bias, ICLTensor *output, int result_fixedpoint_multiplier, int result_shift, int result_offset_after_shift,
                    int min = 0, int max = 0);
+    /** Initialise the kernel's input and output.
+     *
+     * @param[in]  compile_context              The compile context to be used.
+     * @param[in]  input                        Input tensor. Data type supported: S32
+     * @param[in]  bias                         Biases tensor. Only shared biases supported and it can be a nullptr if the biases addition is not required.
+     *                                          Biases are 1D tensor with dimensions [OFM]. Data type supported: Same as @p input.
+     * @param[out] output                       Output tensor. Data type supported: Data type supported: QASYMM8_SIGNED
+     * @param[in]  result_fixedpoint_multiplier Fixed point value to be multiplied to each element of the input matrix when once the result_offset has been add
+     * @param[in]  result_shift                 Integer value used to round to nearest division by a power-of-two the result after the fixed point multiplication
+     * @param[in]  result_offset_after_shift    Offset to be applied to result before converting it back to QASYMM8_SIGNED
+     * @param[in]  min                          (Optional) Min value used to saturate down the output result before converting back to QASYMM8_SIGNED. Defaults to 0
+     * @param[in]  max                          (Optional) Max value used to saturate up the output result before converting back to QASYMM8_SIGNED. Defaults to 0
+     *                                          Along with @p min, this value can be used to implement "rectified linear unit" activation functions
+     */
+    void configure(CLCompileContext &compile_context, const ICLTensor *input, const ICLTensor *bias, ICLTensor *output, int result_fixedpoint_multiplier, int result_shift, int result_offset_after_shift,
+                   int min = 0, int max = 0);
     /** Static function to check if given info will lead to a valid configuration of @ref CLGEMMLowpQuantizeDownInt32ToUint8ScaleByFixedPointKernel
      *
      * @param[in] input  Input tensor. Data type supported: S32
diff --git a/arm_compute/core/CL/kernels/CLGEMMLowpQuantizeDownInt32ToUint8ScaleByFixedPointKernel.h b/arm_compute/core/CL/kernels/CLGEMMLowpQuantizeDownInt32ToUint8ScaleByFixedPointKernel.h
index e8066e0..e319c32 100644
--- a/arm_compute/core/CL/kernels/CLGEMMLowpQuantizeDownInt32ToUint8ScaleByFixedPointKernel.h
+++ b/arm_compute/core/CL/kernels/CLGEMMLowpQuantizeDownInt32ToUint8ScaleByFixedPointKernel.h
@@ -1,5 +1,5 @@
 /*
- * Copyright (c) 2017-2019 ARM Limited.
+ * Copyright (c) 2017-2020 ARM Limited.
  *
  * SPDX-License-Identifier: MIT
  *
@@ -70,6 +70,22 @@
      */
     void configure(const ICLTensor *input, const ICLTensor *bias, ICLTensor *output, int result_fixedpoint_multiplier, int result_shift, int result_offset_after_shift,
                    int min = 0, int max = 0);
+    /** Initialise the kernel's input and output.
+     *
+     * @param[in]  compile_context              The compile context to be used.
+     * @param[in]  input                        Input tensor. Data type supported: S32
+     * @param[in]  bias                         Biases tensor. Only shared biases supported and it can be a nullptr if the biases addition is not required.
+     *                                          Biases are 1D tensor with dimensions [OFM]. Data type supported: Same as @p input.
+     * @param[out] output                       Output tensor. Data type supported: Data type supported: QASYMM8
+     * @param[in]  result_fixedpoint_multiplier Fixed point value to be multiplied to each element of the input matrix when once the result_offset has been add
+     * @param[in]  result_shift                 Integer value used to round to nearest division by a power-of-two the result after the fixed point multiplication
+     * @param[in]  result_offset_after_shift    Offset to be applied to result before converting it back to QASYMM8
+     * @param[in]  min                          (Optional) Min value used to saturate down the output result before converting back to QASYMM8
+     * @param[in]  max                          (Optional) Max value used to saturate up the output result before converting back to QASYMM8,
+     *                                          Along with @p min, this value can be used to implement "rectified linear unit" activation functions
+     */
+    void configure(CLCompileContext &compile_context, const ICLTensor *input, const ICLTensor *bias, ICLTensor *output, int result_fixedpoint_multiplier, int result_shift, int result_offset_after_shift,
+                   int min = 0, int max = 0);
     /** Static function to check if given info will lead to a valid configuration of @ref CLGEMMLowpQuantizeDownInt32ToUint8ScaleByFixedPointKernel
      *
      * @param[in] input  Input tensor. Data type supported: S32
diff --git a/arm_compute/core/CL/kernels/CLGEMMLowpReductionKernel.h b/arm_compute/core/CL/kernels/CLGEMMLowpReductionKernel.h
index 71681cf..4b610fa 100644
--- a/arm_compute/core/CL/kernels/CLGEMMLowpReductionKernel.h
+++ b/arm_compute/core/CL/kernels/CLGEMMLowpReductionKernel.h
@@ -57,6 +57,18 @@
      *                    - mul_byscalar True if each reduced column/row must be multiplied by a scalar value.
      */
     virtual void configure(const ICLTensor *input, ICLTensor *output, const GEMMLowpReductionKernelInfo &info) = 0;
+    /** Initialise the kernel's input and output.
+     *
+     * @param[in]  compile_context The compile context to be used.
+     * @param[in]  input           Input tensor. Data type supported: S8
+     * @param[out] output          Output row-vector of sums of all the entries in each row/col of input tensor. Data type supported: S32
+     * @param[in]  info            Kernel metadata:
+     *                             - k            Number of matrix columns/rows depending on the type of reduction.
+     *                             - is_reshaped  True if the matrix has been reshaped.
+     *                             - scalar       Scalar value to multiply each reduced column/row by.
+     *                             - mul_byscalar True if each reduced column/row must be multiplied by a scalar value.
+     */
+    virtual void configure(CLCompileContext &compile_context, const ICLTensor *input, ICLTensor *output, const GEMMLowpReductionKernelInfo &info) = 0;
 
 protected:
     const ICLTensor *_input;
@@ -82,6 +94,18 @@
      *                            - mul_byscalar True if each reduced column/row must be multiplied by a scalar value.
      */
     void configure(const ICLTensor *mtx_a, ICLTensor *vector_sum_row, const GEMMLowpReductionKernelInfo &info) override;
+    /** Initialise the kernel's input and output.
+     *
+     * @param[in]  compile_context The compile context to be used.
+     * @param[in]  mtx_a           Input tensor. Data type supported: QASYMM8/QASYMM8_SIGNED
+     * @param[out] vector_sum_row  Output row-vector of sums of all the entries in each row of mtx_a. Data type supported: S32
+     * @param[in]  info            Kernel metadata:
+     *                             - k            Number of matrix columns/rows depending on the type of reduction.
+     *                             - is_reshaped  True if the matrix has been reshaped.
+     *                             - scalar       Scalar value to multiply each reduced column/row by.
+     *                             - mul_byscalar True if each reduced column/row must be multiplied by a scalar value.
+     */
+    void configure(CLCompileContext &compile_context, const ICLTensor *mtx_a, ICLTensor *vector_sum_row, const GEMMLowpReductionKernelInfo &info) override;
     /** Static function to check if given info will lead to a valid configuration of @ref CLGEMMLowpMatrixAReductionKernel
      *
      * @param[in] mtx_a          Input tensor. Data type supported: QASYMM8/QASYMM8_SIGNED
@@ -119,6 +143,18 @@
      *                            - mul_byscalar True if each reduced column/row must be multiplied by a scalar value.
      */
     void configure(const ICLTensor *mtx_b, ICLTensor *vector_sum_col, const GEMMLowpReductionKernelInfo &info) override;
+    /** Initialise the kernel's input and output.
+     *
+     * @param[in]  compile_context The compile context to be used.
+     * @param[in]  mtx_b           Input tensor. Data type supported: Data type supported: QASYMM8/QASYMM8_SIGNED
+     * @param[out] vector_sum_col  Output row-vector of sums of all the entries in each column of mtx_b. Data type supported: S32
+     * @param[in]  info            Kernel metadata:
+     *                             - k            Number of matrix columns/rows depending on the type of reduction.
+     *                             - is_reshaped  True if the matrix has been reshaped.
+     *                             - scalar       Scalar value to multiply each reduced column/row by.
+     *                             - mul_byscalar True if each reduced column/row must be multiplied by a scalar value.
+     */
+    void configure(CLCompileContext &compile_context, const ICLTensor *mtx_b, ICLTensor *vector_sum_col, const GEMMLowpReductionKernelInfo &info) override;
     /** Static function to check if given info will lead to a valid configuration of @ref CLGEMMLowpMatrixBReductionKernel
      *
      * @param[in] mtx_b          Input tensor. Data type supported: Data type supported: QASYMM8/QASYMM8_SIGNED
diff --git a/arm_compute/core/CL/kernels/CLGEMMMatrixAccumulateBiasesKernel.h b/arm_compute/core/CL/kernels/CLGEMMMatrixAccumulateBiasesKernel.h
index bff419c..037ec4d 100644
--- a/arm_compute/core/CL/kernels/CLGEMMMatrixAccumulateBiasesKernel.h
+++ b/arm_compute/core/CL/kernels/CLGEMMMatrixAccumulateBiasesKernel.h
@@ -1,5 +1,5 @@
 /*
- * Copyright (c) 2017-2019 ARM Limited.
+ * Copyright (c) 2017-2020 ARM Limited.
  *
  * SPDX-License-Identifier: MIT
  *
@@ -50,6 +50,13 @@
      * @param[in]      biases The shared biases tensor to append. It must be 1D tensor. Data types supported: Same as @p input
      */
     void configure(ICLTensor *accum, const ICLTensor *biases);
+    /** Set the accumulate buffer and the biases of the kernel.
+     *
+     * @param[in]      compile_context The compile context to be used.
+     * @param[in, out] accum           The accumulate tensor to convert. Data types supported: F16/F32
+     * @param[in]      biases          The shared biases tensor to append. It must be 1D tensor. Data types supported: Same as @p input
+     */
+    void configure(CLCompileContext &compile_context, ICLTensor *accum, const ICLTensor *biases);
     /** Static function to check if given info will lead to a valid configuration of @ref CLGEMMMatrixAccumulateBiasesKernel
      *
      * @param[in] accum      The accumulate tensor to convert. Data types supported: F16/F32
diff --git a/arm_compute/core/CL/kernels/CLGEMMMatrixMultiplyKernel.h b/arm_compute/core/CL/kernels/CLGEMMMatrixMultiplyKernel.h
index 82c4091..fe34735 100644
--- a/arm_compute/core/CL/kernels/CLGEMMMatrixMultiplyKernel.h
+++ b/arm_compute/core/CL/kernels/CLGEMMMatrixMultiplyKernel.h
@@ -1,5 +1,5 @@
 /*
- * Copyright (c) 2017-2019 ARM Limited.
+ * Copyright (c) 2017-2020 ARM Limited.
  *
  * SPDX-License-Identifier: MIT
  *
@@ -68,6 +68,23 @@
      */
     void configure(const ICLTensor *input0, const ICLTensor *input1, const ICLTensor *input2, ICLTensor *output, float alpha, float beta = 0.f,
                    bool is_interleaved_transposed = true, const GEMMReshapeInfo &reshape_info = GEMMReshapeInfo(), bool fp_mixed_precision = false, const ActivationLayerInfo &activation_info = ActivationLayerInfo());
+    /** Initialise the kernel's input, output and alpha
+     *
+     * @param[in]  compile_context           The compile context to be used.
+     * @param[in]  input0                    Input tensor containing the Matrix A. Data types supported: F16/F32
+     * @param[in]  input1                    Input tensor containing the Matrix B. Data type supported: same as @p input0
+     * @param[in]  input2                    Input tensor containing the Matrix C (bias). Can be nullptr. Data type supported: same as @p input0
+     * @param[out] output                    Output tensor to store the result of matrix multiplication. Data type supported: same as @p input0
+     * @param[in]  alpha                     Weight of the matrix product
+     * @param[in]  beta                      (Optional) Weight of vector C. Default value is 0. Only beta = 1 is currently supported.
+     * @param[in]  is_interleaved_transposed (Optional) True if input0 and input1 have been reshaped respectively using @ref CLGEMMReshapeLHSMatrixKernel and @ref CLGEMMReshapeRHSMatrixKernel
+     * @param[in]  reshape_info              (Optional) GEMM reshape info. If is_interleaved_transposed = true, this object must contain the information to understand how the matrix A and matrix B have been reshaped
+     * @param[in]  fp_mixed_precision        (Optional) Use wider accumulators (32 bit instead of 16 for FP16) to improve accuracy
+     * @param[in]  activation_info           (Optional) Activation to apply after the matrix multiplication
+     *
+     */
+    void configure(CLCompileContext &compile_context, const ICLTensor *input0, const ICLTensor *input1, const ICLTensor *input2, ICLTensor *output, float alpha, float beta = 0.f,
+                   bool is_interleaved_transposed = true, const GEMMReshapeInfo &reshape_info = GEMMReshapeInfo(), bool fp_mixed_precision = false, const ActivationLayerInfo &activation_info = ActivationLayerInfo());
     /** Static function to check if given info will lead to a valid configuration of @ref CLGEMMMatrixMultiplyKernel
      *
      * @param[in] input0                    Input tensor containing the Matrix A info. Data types supported: F16/F32
diff --git a/arm_compute/core/CL/kernels/CLGEMMMatrixMultiplyNativeKernel.h b/arm_compute/core/CL/kernels/CLGEMMMatrixMultiplyNativeKernel.h
index 9bac8c9..370ef8b 100644
--- a/arm_compute/core/CL/kernels/CLGEMMMatrixMultiplyNativeKernel.h
+++ b/arm_compute/core/CL/kernels/CLGEMMMatrixMultiplyNativeKernel.h
@@ -1,5 +1,5 @@
 /*
- * Copyright (c) 2019 ARM Limited.
+ * Copyright (c) 2019-2020 ARM Limited.
  *
  * SPDX-License-Identifier: MIT
  *
@@ -65,6 +65,27 @@
     void configure(const ICLTensor *input0, const ICLTensor *input1, const ICLTensor *input2, ICLTensor *output, float alpha, float beta, const GEMMLHSMatrixInfo &lhs_info,
                    const GEMMRHSMatrixInfo &rhs_info,
                    const GEMMKernelInfo    &gemm_info);
+    /** Initialise the kernel's input and output.
+     *
+     * @param[in]  compile_context The compile context to be used.
+     * @param[in]  input0          Input tensor for the LHS matrix. Data type supported: F32. The number of dimensions for the LHS matrix must be less or equal than 4.
+     * @param[in]  input1          Input tensor for the RHS matrix. Data type supported: same as @p input0. The number of dimensions for the RHS matrix must be less or equal than 3.
+     * @param[in]  input2          Input tensor containing the bias matrix. Data type supported: same as @p input0.
+     * @param[out] output          Output tensor info. Data type supported: same as @p input0
+     * @param[in]  alpha           Weight of the matrix product
+     * @param[in]  beta            Weight of the matrix bias
+     * @param[in]  lhs_info        LHS matrix information used to retrieve the number of rows and accumulations to be processed by each thread. Only the following values are supported:
+     *                             lhs_info.m0: 1,2,3,4,5,6,7,8
+     *                             lhs_info.k0: 2,3,4,8,16
+     * @param[in]  rhs_info        RHS matrix information used to retrieve the number of columns and accumulations to be processed by each thread. Only the following values are supported:
+     *                             rhs_info.n0: 2,3,4,8,16
+     *                             rhs_info.k0: same of lhs_info.k0
+     * @param[in]  gemm_info       GEMM information used to retrieve the original dimensions of the input matrices
+     */
+    void configure(CLCompileContext &compile_context, const ICLTensor *input0, const ICLTensor *input1, const ICLTensor *input2, ICLTensor *output, float alpha, float beta,
+                   const GEMMLHSMatrixInfo &lhs_info,
+                   const GEMMRHSMatrixInfo &rhs_info,
+                   const GEMMKernelInfo    &gemm_info);
     /** Static function to check if given info will lead to a valid configuration of @ref CLGEMMMatrixMultiplyNativeKernel
      *
      * @param[in] input0    Input tensor info for the LHS matrix. Data type supported: F32. The number of dimensions for the LHS matrix must be less or equal than 4.
diff --git a/arm_compute/core/CL/kernels/CLGEMMMatrixMultiplyReshapedKernel.h b/arm_compute/core/CL/kernels/CLGEMMMatrixMultiplyReshapedKernel.h
index 449c333..45df676 100644
--- a/arm_compute/core/CL/kernels/CLGEMMMatrixMultiplyReshapedKernel.h
+++ b/arm_compute/core/CL/kernels/CLGEMMMatrixMultiplyReshapedKernel.h
@@ -1,5 +1,5 @@
 /*
- * Copyright (c) 2018-2019 ARM Limited.
+ * Copyright (c) 2018-2020 ARM Limited.
  *
  * SPDX-License-Identifier: MIT
  *
@@ -76,6 +76,35 @@
     void configure(const ICLTensor *input0, const ICLTensor *input1, const ICLTensor *input2, ICLTensor *output, float alpha, float beta, const GEMMLHSMatrixInfo &lhs_info,
                    const GEMMRHSMatrixInfo &rhs_info,
                    const GEMMKernelInfo    &gemm_info);
+    /** Initialise the kernel's input and output.
+     *
+     * @note The F16 computation also supports mixed precision through the gemm_info.fp_mixed_precision flag.
+     *       Mixed precision combines different floating precisions during the computation, in particular, F32 for the accumulations and F16 for the
+     *       multiplications. i.e. float c = (half)a * (half)b
+     *
+     * @param[in]  compile_context The compile context to be used.
+     * @param[in]  input0          Input tensor containing the LHS reshaped matrix. Data type supported: F16/F32. The number of dimensions for the LHS matrix must be less or equal than 4
+     * @param[in]  input1          Input tensor containing the RHS reshaped matrix. Data type supported: same as @p input0. The number of dimensions for the RHS matrix must be less or equal than 3
+     * @param[in]  input2          Input tensor containing the bias matrix. Data type supported: same as @p input0.
+     * @param[out] output          Output tensor to store the result of matrix multiplication. Data type supported: same as @p input0
+     * @param[in]  alpha           Weight of the matrix product
+     * @param[in]  beta            Weight of the matrix bias
+     * @param[in]  lhs_info        LHS matrix information used for reshaping the input0 tensor.  Only the following values are supported:
+     *                             lhs_info.m0: 2,3,4,5,6,7,8
+     *                             lhs_info.k0: 2,3,4,8,16
+     *                             lhs_info.transpose: false
+     * @param[in]  rhs_info        RHS matrix information used for reshaping the input1 tensor.  Only the following values are supported:
+     *                             rhs_info.n0: 2,3,4,8,16
+     *                             rhs_info.k0: 2,3,4,8,16
+     *                             rhs_info.transpose: true
+     * @param[in]  gemm_info       GEMM information used to retrieve the original dimensions of the input matrices
+     *
+     * @note lhs_info.k0 must be equal to rhs_info.k0
+     */
+    void configure(CLCompileContext &compile_context, const ICLTensor *input0, const ICLTensor *input1, const ICLTensor *input2, ICLTensor *output, float alpha, float beta,
+                   const GEMMLHSMatrixInfo &lhs_info,
+                   const GEMMRHSMatrixInfo &rhs_info,
+                   const GEMMKernelInfo    &gemm_info);
     /** Static function to check if given info will lead to a valid configuration of @ref CLGEMMMatrixMultiplyReshapedKernel
      *
      * @param[in] input0    Input tensor containing the LHS reshaped matrix. Data type supported: F16/F32. The number of dimensions for the LHS matrix must be less or equal than 4
diff --git a/arm_compute/core/CL/kernels/CLGEMMMatrixMultiplyReshapedOnlyRHSKernel.h b/arm_compute/core/CL/kernels/CLGEMMMatrixMultiplyReshapedOnlyRHSKernel.h
index b91b7ee..b6285dd 100644
--- a/arm_compute/core/CL/kernels/CLGEMMMatrixMultiplyReshapedOnlyRHSKernel.h
+++ b/arm_compute/core/CL/kernels/CLGEMMMatrixMultiplyReshapedOnlyRHSKernel.h
@@ -1,5 +1,5 @@
 /*
- * Copyright (c) 2019 ARM Limited.
+ * Copyright (c) 2019-2020 ARM Limited.
  *
  * SPDX-License-Identifier: MIT
  *
@@ -68,6 +68,27 @@
     void configure(const ICLTensor *input0, const ICLTensor *input1, const ICLTensor *input2, ICLTensor *output, float alpha, float beta, const GEMMLHSMatrixInfo &lhs_info,
                    const GEMMRHSMatrixInfo &rhs_info,
                    const GEMMKernelInfo    &gemm_info);
+    /** Initialise the kernel's input and output.
+     *
+     * @param[in]  compile_context The compile context to be used.
+     * @param[in]  input0          Input tensor containing the LHS matrix. Data type supported: F16/F32. The number of dimensions for the LHS matrix must be less or equal than 4.
+     * @param[in]  input1          Input tensor containing the RHS reshaped matrix. Data type supported: same as @p input0. The number of dimensions for the RHS matrix must be less or equal than 3.
+     * @param[in]  input2          Input tensor containing the bias matrix. Data type supported: same as @p input0.
+     * @param[out] output          Output tensor to store the result of matrix multiplication. Data type supported: same as @p input0
+     * @param[in]  alpha           Weight of the matrix product
+     * @param[in]  beta            Weight of the matrix bias
+     * @param[in]  lhs_info        LHS matrix information used to retrieve the number of rows to be processed by each thread. Only the following values are supported:
+     *                             lhs_info.m0: 1,2,3,4,5,6,7,8
+     * @param[in]  rhs_info        RHS matrix information used for reshaping the input1 tensor.  Only the following values are supported:
+     *                             rhs_info.k0: 2,3,4,8,16
+     *                             rhs_info.n0: 2,3,4,8,16
+     *                             rhs_info.transpose: true,false
+     * @param[in]  gemm_info       GEMM information used to retrieve the original dimensions of the input matrices
+     */
+    void configure(CLCompileContext &compile_context, const ICLTensor *input0, const ICLTensor *input1, const ICLTensor *input2, ICLTensor *output, float alpha, float beta,
+                   const GEMMLHSMatrixInfo &lhs_info,
+                   const GEMMRHSMatrixInfo &rhs_info,
+                   const GEMMKernelInfo    &gemm_info);
     /** Static function to check if given info will lead to a valid configuration of @ref CLGEMMMatrixMultiplyReshapedOnlyRHSKernel
      *
      * @param[in] input0    Input tensor info for the LHS matrix. Data type supported: F16/F32. The number of dimensions for the LHS matrix must be less or equal than 4.
diff --git a/arm_compute/core/CL/kernels/CLGEMMMatrixVectorMultiplyKernel.h b/arm_compute/core/CL/kernels/CLGEMMMatrixVectorMultiplyKernel.h
index 8ee911d..f31c5c2 100644
--- a/arm_compute/core/CL/kernels/CLGEMMMatrixVectorMultiplyKernel.h
+++ b/arm_compute/core/CL/kernels/CLGEMMMatrixVectorMultiplyKernel.h
@@ -51,6 +51,14 @@
      * @param[out] output The output 2D tensor. Data types supported: Same as @p input, S32 for QASYMM8/QASYMM8_SIGNED.
      */
     void configure(const ICLTensor *input0, const ICLTensor *input1, ICLTensor *output);
+    /** Set the input and output of the kernel.
+     *
+     * @param[in]  compile_context The compile context to be used.
+     * @param[in]  input0          The reshaped input tensor. Data types supported: QASYMM8/QASYMM8_SIGNED/F16/F32
+     * @param[in]  input1          The 2D reshaped weights tensor. Data type supported: Same as @p input.
+     * @param[out] output          The output 2D tensor. Data types supported: Same as @p input, S32 for QASYMM8/QASYMM8_SIGNED.
+     */
+    void configure(CLCompileContext &compile_context, const ICLTensor *input0, const ICLTensor *input1, ICLTensor *output);
     /** Static function to check if given info will lead to a valid configuration of @ref CLGEMMMatrixVectorMultiplyKernel
      *
      * @param[in] input0 The reshaped input tensor info. Data types supported: QASYMM8/QASYMM8_SIGNED/F16/F32
diff --git a/arm_compute/core/CL/kernels/CLGEMMReshapeLHSMatrixKernel.h b/arm_compute/core/CL/kernels/CLGEMMReshapeLHSMatrixKernel.h
index 7955b95..e8e02ac 100644
--- a/arm_compute/core/CL/kernels/CLGEMMReshapeLHSMatrixKernel.h
+++ b/arm_compute/core/CL/kernels/CLGEMMReshapeLHSMatrixKernel.h
@@ -61,6 +61,21 @@
      * @param[in]  reinterpret_input_as_3d (Optional) True if the input has to be reinterpreted as 3D tensor
      */
     void configure(const ICLTensor *input, ICLTensor *output, const GEMMLHSMatrixInfo &lhs_info, bool reinterpret_input_as_3d = false);
+    /** Initialise the kernel's input and output.
+     *
+     * @param[in]  compile_context         The compile context to be used.
+     * @param[in]  input                   Input tensor. Data types supported: All
+     * @param[out] output                  Output tensor. Data type supported: same as @p input
+     * @param[in]  lhs_info                LHS matrix information to be used for reshaping. This object contains all the necessary
+     *                                     information to reshape the input tensor. Only the following values are supported:
+     *                                     lhs_info.m0: 2,3,4,5,6,7,8
+     *                                     lhs_info.k0: 2,3,4,8,16
+     *                                     lhs_info.v0: greater than 0
+     *                                     lhs_info.transpose: true, false
+     *                                     lhs_info.interleave: true, false
+     * @param[in]  reinterpret_input_as_3d (Optional) True if the input has to be reinterpreted as 3D tensor
+     */
+    void configure(CLCompileContext &compile_context, const ICLTensor *input, ICLTensor *output, const GEMMLHSMatrixInfo &lhs_info, bool reinterpret_input_as_3d = false);
     /** Static function to check if given info will lead to a valid configuration of @ref CLGEMMReshapeLHSMatrixKernel
      *
      * @param[in] input                   Input tensor info. Data types supported: All
diff --git a/arm_compute/core/CL/kernels/CLGEMMReshapeRHSMatrixKernel.h b/arm_compute/core/CL/kernels/CLGEMMReshapeRHSMatrixKernel.h
index 19acd1f..ada8889 100644
--- a/arm_compute/core/CL/kernels/CLGEMMReshapeRHSMatrixKernel.h
+++ b/arm_compute/core/CL/kernels/CLGEMMReshapeRHSMatrixKernel.h
@@ -1,5 +1,5 @@
 /*
- * Copyright (c) 2018-2019 ARM Limited.
+ * Copyright (c) 2018-2020 ARM Limited.
  *
  * SPDX-License-Identifier: MIT
  *
@@ -59,6 +59,20 @@
      *                      rhs_info.interleave: true, false
      */
     void configure(const ICLTensor *input, ICLTensor *output, const GEMMRHSMatrixInfo &rhs_info);
+    /** Initialise the kernel's input and output.
+     *
+     * @param[in]  compile_context The compile context to be used.
+     * @param[in]  input           Input tensor. Data types supported: All
+     * @param[out] output          Output tensor. Data type supported: same as @p input
+     * @param[in]  rhs_info        RHS matrix information to be used for reshaping. This object contains all the necessary
+     *                             information to reshape the input tensor. Only the following values are supported:
+     *                             rhs_info.n0: 2,3,4,8,16
+     *                             rhs_info.k0: 1,2,3,4,8,16 (k0 = 1 only if rhs_info.transpose = false)
+     *                             rhs_info.h0: greater than 0
+     *                             rhs_info.transpose: true, false
+     *                             rhs_info.interleave: true, false
+     */
+    void configure(CLCompileContext &compile_context, const ICLTensor *input, ICLTensor *output, const GEMMRHSMatrixInfo &rhs_info);
     /** Static function to check if given info will lead to a valid configuration of @ref CLGEMMReshapeRHSMatrixKernel
      *
      * @param[in] input    Input tensor info. Data types supported: All
diff --git a/arm_compute/core/CL/kernels/CLGatherKernel.h b/arm_compute/core/CL/kernels/CLGatherKernel.h
index 937d744..c91b95d 100644
--- a/arm_compute/core/CL/kernels/CLGatherKernel.h
+++ b/arm_compute/core/CL/kernels/CLGatherKernel.h
@@ -55,6 +55,15 @@
      * @param[in]  axis    (Optional) The axis in @p input to gather @p indices from. Negative values wrap around. Defaults to 0
      */
     void configure(const ICLTensor *input, const ICLTensor *indices, ICLTensor *output, int axis = 0);
+    /** Initialise the kernel's inputs and outputs
+     *
+     * @param[in]  compile_context The compile context to be used.
+     * @param[in]  input           Source tensor. Supported tensor rank: up to 4. Data type supported: All.
+     * @param[in]  indices         Indices tensor. Supported tensor rank: up to 1. Must be one of the following types: U32/S32. Each value must be in range [0, input.shape[@p axis])
+     * @param[out] output          Destination tensor. Data type supported: Same as @p input
+     * @param[in]  axis            (Optional) The axis in @p input to gather @p indices from. Negative values wrap around. Defaults to 0
+     */
+    void configure(CLCompileContext &compile_context, const ICLTensor *input, const ICLTensor *indices, ICLTensor *output, int axis = 0);
 
     /** Static function to check if given info will lead to a valid configuration of @ref CLGatherKernel
      *
diff --git a/arm_compute/core/CL/kernels/CLGaussian3x3Kernel.h b/arm_compute/core/CL/kernels/CLGaussian3x3Kernel.h
index f377c52..7eb7f7a 100644
--- a/arm_compute/core/CL/kernels/CLGaussian3x3Kernel.h
+++ b/arm_compute/core/CL/kernels/CLGaussian3x3Kernel.h
@@ -1,5 +1,5 @@
 /*
- * Copyright (c) 2016-2019 ARM Limited.
+ * Copyright (c) 2016-2020 ARM Limited.
  *
  * SPDX-License-Identifier: MIT
  *
@@ -43,6 +43,14 @@
      * @param[in]  border_undefined True if the border mode is undefined. False if it's replicate or constant.
      */
     void configure(const ICLTensor *input, ICLTensor *output, bool border_undefined);
+    /** Initialise the kernel's input and output.
+     *
+     * @param[in]  compile_context  The compile context to be used.
+     * @param[in]  input            An input tensor. Data types supported: U8
+     * @param[out] output           The output tensor. Data types supported: U8.
+     * @param[in]  border_undefined True if the border mode is undefined. False if it's replicate or constant.
+     */
+    void configure(CLCompileContext &compile_context, const ICLTensor *input, ICLTensor *output, bool border_undefined);
 
     // Inherited methods overridden:
     BorderSize border_size() const override;
diff --git a/arm_compute/core/CL/kernels/CLGaussian5x5Kernel.h b/arm_compute/core/CL/kernels/CLGaussian5x5Kernel.h
index 4d0402d..37a7727 100644
--- a/arm_compute/core/CL/kernels/CLGaussian5x5Kernel.h
+++ b/arm_compute/core/CL/kernels/CLGaussian5x5Kernel.h
@@ -1,5 +1,5 @@
 /*
- * Copyright (c) 2016-2019 ARM Limited.
+ * Copyright (c) 2016-2020 ARM Limited.
  *
  * SPDX-License-Identifier: MIT
  *
@@ -41,6 +41,14 @@
      * @param[in]  border_undefined True if the border mode is undefined. False if it's replicate or constant.
      */
     void configure(const ICLTensor *input, ICLTensor *output, bool border_undefined);
+    /** Initialise the kernel's source, destination and border.
+     *
+     * @param[in]  compile_context  The compile context to be used.
+     * @param[in]  input            Source tensor. Data types supported: U8.
+     * @param[out] output           Destination tensor. Data types supported: S16.
+     * @param[in]  border_undefined True if the border mode is undefined. False if it's replicate or constant.
+     */
+    void configure(CLCompileContext &compile_context, const ICLTensor *input, ICLTensor *output, bool border_undefined);
 
 private:
     //Make the configure method of the parent class private
@@ -58,6 +66,14 @@
      * @param[in]  border_undefined True if the border mode is undefined. False if it's replicate or constant.
      */
     void configure(const ICLTensor *input, ICLTensor *output, bool border_undefined);
+    /** Initialise the kernel's source, destination and border.
+     *
+     * @param[in]  compile_context  The compile context to be used.
+     * @param[in]  input            Input tensor(output of horizontal pass). Data types supported: S16.
+     * @param[out] output           Destination tensor. Data types supported: U8.
+     * @param[in]  border_undefined True if the border mode is undefined. False if it's replicate or constant.
+     */
+    void configure(CLCompileContext &compile_context, const ICLTensor *input, ICLTensor *output, bool border_undefined);
 
 private:
     //Make the configure method of the parent class private
diff --git a/arm_compute/core/CL/kernels/CLGaussianPyramidKernel.h b/arm_compute/core/CL/kernels/CLGaussianPyramidKernel.h
index a3623f1..5acd7fd 100644
--- a/arm_compute/core/CL/kernels/CLGaussianPyramidKernel.h
+++ b/arm_compute/core/CL/kernels/CLGaussianPyramidKernel.h
@@ -1,5 +1,5 @@
 /*
- * Copyright (c) 2017-2019 ARM Limited.
+ * Copyright (c) 2017-2020 ARM Limited.
  *
  * SPDX-License-Identifier: MIT
  *
@@ -53,6 +53,13 @@
      * @param[out] output Destination tensor. Output should have half the input width. Data types supported: U16.
      */
     void configure(const ICLTensor *input, ICLTensor *output);
+    /** Initialise the kernel's source, destination and border mode.
+     *
+     * @param[in]  compile_context The compile context to be used.
+     * @param[in]  input           Source tensor. Data types supported: U8.
+     * @param[out] output          Destination tensor. Output should have half the input width. Data types supported: U16.
+     */
+    void configure(CLCompileContext &compile_context, const ICLTensor *input, ICLTensor *output);
 
     // Inherited methods overridden:
     void run(const Window &window, cl::CommandQueue &queue) override;
@@ -85,6 +92,13 @@
      * @param[out] output Destination tensor. Output should have half the input height. Data types supported: U8.
      */
     void configure(const ICLTensor *input, ICLTensor *output);
+    /** Initialise the kernel's source, destination and border mode.
+     *
+     * @param[in]  compile_context The compile context to be used.
+     * @param[in]  input           Source tensor. Data types supported: U16.
+     * @param[out] output          Destination tensor. Output should have half the input height. Data types supported: U8.
+     */
+    void configure(CLCompileContext &compile_context, const ICLTensor *input, ICLTensor *output);
 
     // Inherited methods overridden:
     void run(const Window &window, cl::CommandQueue &queue) override;
diff --git a/arm_compute/core/CL/kernels/CLGenerateProposalsLayerKernel.h b/arm_compute/core/CL/kernels/CLGenerateProposalsLayerKernel.h
index abd39a4..abac4b7 100644
--- a/arm_compute/core/CL/kernels/CLGenerateProposalsLayerKernel.h
+++ b/arm_compute/core/CL/kernels/CLGenerateProposalsLayerKernel.h
@@ -1,5 +1,5 @@
 /*
- * Copyright (c) 2019 ARM Limited.
+ * Copyright (c) 2019-2020 ARM Limited.
  *
  * SPDX-License-Identifier: MIT
  *
@@ -54,6 +54,15 @@
      *
      */
     void configure(const ICLTensor *anchors, ICLTensor *all_anchors, const ComputeAnchorsInfo &info);
+    /** Set the input and output tensors.
+     *
+     * @param[in]  compile_context The compile context to be used.
+     * @param[in]  anchors         Source tensor. Original set of anchors of size (4, A), where A is the number of anchors. Data types supported: QSYMM16/F16/F32
+     * @param[out] all_anchors     Destination tensor. Destination anchors of size (4, H*W*A) where H and W are the height and width of the feature map and A is the number of anchors. Data types supported: Same as @p input
+     * @param[in]  info            Contains Compute Anchors operation information described in @ref ComputeAnchorsInfo
+     *
+     */
+    void configure(CLCompileContext &compile_context, const ICLTensor *anchors, ICLTensor *all_anchors, const ComputeAnchorsInfo &info);
 
     /** Static function to check if given info will lead to a valid configuration of @ref CLComputeAllAnchorsKernel
      *
diff --git a/arm_compute/core/CL/kernels/CLHOGDescriptorKernel.h b/arm_compute/core/CL/kernels/CLHOGDescriptorKernel.h
index fb2019a..1b1610e 100644
--- a/arm_compute/core/CL/kernels/CLHOGDescriptorKernel.h
+++ b/arm_compute/core/CL/kernels/CLHOGDescriptorKernel.h
@@ -1,5 +1,5 @@
 /*
- * Copyright (c) 2017-2019 ARM Limited.
+ * Copyright (c) 2017-2020 ARM Limited.
  *
  * SPDX-License-Identifier: MIT
  *
@@ -57,6 +57,15 @@
      * @param[in]  hog_info        HOG's metadata
      */
     void configure(const ICLTensor *input_magnitude, const ICLTensor *input_phase, ICLTensor *output, const HOGInfo *hog_info);
+    /**  Initialise the kernel's inputs, output and HOG's metadata
+     *
+     * @param[in]  compile_context The compile context to be used.
+     * @param[in]  input_magnitude Input tensor which stores the magnitude of the gradient for each pixel. Data type supported: S16.
+     * @param[in]  input_phase     Input tensor which stores the phase of the gradient for each pixel. Data type supported: U8
+     * @param[out] output          Output tensor which stores the local HOG for each cell. DataType supported: F32. Number of channels supported: equal to the number of histogram bins per cell
+     * @param[in]  hog_info        HOG's metadata
+     */
+    void configure(CLCompileContext &compile_context, const ICLTensor *input_magnitude, const ICLTensor *input_phase, ICLTensor *output, const HOGInfo *hog_info);
 
     // Inherited methods overridden:
     void run(const Window &window, cl::CommandQueue &queue) override;
@@ -92,6 +101,14 @@
      * @param[in]  hog_info HOG's metadata
      */
     void configure(const ICLTensor *input, ICLTensor *output, const HOGInfo *hog_info);
+    /** Initialise the kernel's input, output and HOG's metadata
+     *
+     * @param[in]  compile_context The compile context to be used.
+     * @param[in]  input           Input tensor which stores the local HOG for each cell. Data type supported: F32. Number of channels supported: equal to the number of histogram bins per cell
+     * @param[out] output          Output tensor which stores the normalised blocks. Data type supported: F32. Number of channels supported: equal to the number of histogram bins per block
+     * @param[in]  hog_info        HOG's metadata
+     */
+    void configure(CLCompileContext &compile_context, const ICLTensor *input, ICLTensor *output, const HOGInfo *hog_info);
 
     // Inherited methods overridden:
     void run(const Window &window, cl::CommandQueue &queue) override;
diff --git a/arm_compute/core/CL/kernels/CLHOGDetectorKernel.h b/arm_compute/core/CL/kernels/CLHOGDetectorKernel.h
index 3018c56..8a32642 100644
--- a/arm_compute/core/CL/kernels/CLHOGDetectorKernel.h
+++ b/arm_compute/core/CL/kernels/CLHOGDetectorKernel.h
@@ -1,5 +1,5 @@
 /*
- * Copyright (c) 2017-2019 ARM Limited.
+ * Copyright (c) 2017-2020 ARM Limited.
  *
  * SPDX-License-Identifier: MIT
  *
@@ -68,6 +68,21 @@
      */
     void configure(const ICLTensor *input, const ICLHOG *hog, ICLDetectionWindowArray *detection_windows, cl::Buffer *num_detection_windows, const Size2D &detection_window_stride, float threshold = 0.0f,
                    uint16_t idx_class = 0);
+    /** Initialise the kernel's input, HOG data-object, detection window, the stride of the detection window, the threshold and index of the object to detect
+     *
+     * @param[in]  compile_context         The compile context to be used.
+     * @param[in]  input                   Input tensor which stores the HOG descriptor obtained with @ref CLHOGOrientationBinningKernel. Data type supported: F32. Number of channels supported: equal to the number of histogram bins per block
+     * @param[in]  hog                     HOG data object used by @ref CLHOGOrientationBinningKernel and  @ref CLHOGBlockNormalizationKernel
+     * @param[out] detection_windows       Array of @ref DetectionWindow. This array stores all the detected objects
+     * @param[in]  num_detection_windows   Number of detected objects
+     * @param[in]  detection_window_stride Distance in pixels between 2 consecutive detection windows in x and y directions.
+     *                                     It must be multiple of the hog->info()->block_stride()
+     * @param[in]  threshold               (Optional) Threshold for the distance between features and SVM classifying plane
+     * @param[in]  idx_class               (Optional) Index of the class used for evaluating which class the detection window belongs to
+     */
+    void configure(CLCompileContext &compile_context, const ICLTensor *input, const ICLHOG *hog, ICLDetectionWindowArray *detection_windows, cl::Buffer *num_detection_windows,
+                   const Size2D &detection_window_stride, float threshold = 0.0f,
+                   uint16_t idx_class = 0);
 
     // Inherited methods overridden:
     void run(const Window &window, cl::CommandQueue &queue);
diff --git a/arm_compute/core/CL/kernels/CLHarrisCornersKernel.h b/arm_compute/core/CL/kernels/CLHarrisCornersKernel.h
index 3591afd..ed91aaf 100644
--- a/arm_compute/core/CL/kernels/CLHarrisCornersKernel.h
+++ b/arm_compute/core/CL/kernels/CLHarrisCornersKernel.h
@@ -1,5 +1,5 @@
 /*
- * Copyright (c) 2016-2019 ARM Limited.
+ * Copyright (c) 2016-2020 ARM Limited.
  *
  * SPDX-License-Identifier: MIT
  *
@@ -67,6 +67,21 @@
     void configure(const ICLImage *input1, const ICLImage *input2, ICLImage *output,
                    int32_t block_size, float norm_factor, float strength_thresh, float sensitivity,
                    bool border_undefined);
+    /** Setup the kernel parameters
+     *
+     * @param[in]  compile_context  The compile context to be used.
+     * @param[in]  input1           Source image (gradient X). Data types supported S16, S32. (Must be the same as input2)
+     * @param[in]  input2           Source image (gradient Y). Data types supported S16, S32. (Must be the same as input1)
+     * @param[out] output           Destination image (harris score). Data types supported F32
+     * @param[in]  block_size       The block window size used to compute the Harris Corner score.  Supports: 3, 5 and 7
+     * @param[in]  norm_factor      Normalization factor to use accordingly with the gradient size (Must be different from 0)
+     * @param[in]  strength_thresh  Minimum threshold with which to eliminate Harris Corner scores (computed using the normalized Sobel kernel).
+     * @param[in]  sensitivity      Sensitivity threshold k from the Harris-Stephens equation.
+     * @param[in]  border_undefined True if the border mode is undefined. False if it's replicate or constant.
+     */
+    void configure(CLCompileContext &compile_context, const ICLImage *input1, const ICLImage *input2, ICLImage *output,
+                   int32_t block_size, float norm_factor, float strength_thresh, float sensitivity,
+                   bool border_undefined);
 
     // Inherited methods overridden:
     void run(const Window &window, cl::CommandQueue &queue) override;
diff --git a/arm_compute/core/CL/kernels/CLHeightConcatenateLayerKernel.h b/arm_compute/core/CL/kernels/CLHeightConcatenateLayerKernel.h
index 5828280..b958959 100644
--- a/arm_compute/core/CL/kernels/CLHeightConcatenateLayerKernel.h
+++ b/arm_compute/core/CL/kernels/CLHeightConcatenateLayerKernel.h
@@ -58,6 +58,15 @@
      *
      */
     void configure(const ICLTensor *input, unsigned int height_offset, ICLTensor *output);
+    /** Initialise the kernel's inputs and output
+     *
+     * @param[in]  compile_context The compile context to be used.
+     * @param[in]  input           Input tensor. Data types supported: All.
+     * @param[in]  height_offset   The starting offset on the Y axis for the output tensor.
+     * @param[out] output          Output tensor. Data types supported: Same as @p input.
+     *
+     */
+    void configure(CLCompileContext &compile_context, const ICLTensor *input, unsigned int height_offset, ICLTensor *output);
     /**  Static function to check if given info will lead to a valid configuration of @ref CLHeightConcatenateLayerKernel
      *
      * @param[in] input         Input tensor info. Data types supported: All.
diff --git a/arm_compute/core/CL/kernels/CLHistogramKernel.h b/arm_compute/core/CL/kernels/CLHistogramKernel.h
index bb1b773..bb0d0b3 100644
--- a/arm_compute/core/CL/kernels/CLHistogramKernel.h
+++ b/arm_compute/core/CL/kernels/CLHistogramKernel.h
@@ -1,5 +1,5 @@
 /*
- * Copyright (c) 2016-2019 ARM Limited.
+ * Copyright (c) 2016-2020 ARM Limited.
  *
  * SPDX-License-Identifier: MIT
  *
@@ -54,6 +54,13 @@
      * @param[out] output Destination distribution.
      */
     void configure(const ICLImage *input, ICLDistribution1D *output);
+    /** Initialise the kernel's input, output and border mode.
+     *
+     * @param[in]  compile_context The compile context to be used.
+     * @param[in]  input           Source image. Data types supported: U8.
+     * @param[out] output          Destination distribution.
+     */
+    void configure(CLCompileContext &compile_context, const ICLImage *input, ICLDistribution1D *output);
 
     // Inherited methods overridden:
     void run(const Window &window, cl::CommandQueue &queue) override;
@@ -85,6 +92,13 @@
      * @param[out] output Destination distribution.
      */
     void configure(const ICLImage *input, ICLDistribution1D *output);
+    /** Initialise the kernel's input, output and border mode.
+     *
+     * @param[in]  compile_context The compile context to be used.
+     * @param[in]  input           Source image. Data types supported: U8.
+     * @param[out] output          Destination distribution.
+     */
+    void configure(CLCompileContext &compile_context, const ICLImage *input, ICLDistribution1D *output);
 
     // Inherited methods overridden:
     void run(const Window &window, cl::CommandQueue &queue) override;
diff --git a/arm_compute/core/CL/kernels/CLIm2ColKernel.h b/arm_compute/core/CL/kernels/CLIm2ColKernel.h
index 95675c8..dddbf8d 100644
--- a/arm_compute/core/CL/kernels/CLIm2ColKernel.h
+++ b/arm_compute/core/CL/kernels/CLIm2ColKernel.h
@@ -80,6 +80,22 @@
      */
     void configure(const ICLTensor *input, ICLTensor *output, const Size2D &kernel_dims, const PadStrideInfo &conv_info, bool has_bias, const Size2D &dilation = Size2D(1U, 1U),
                    unsigned int num_groups = 1);
+    /** Set the input and output of the kernel.
+     *
+     * @param[in]  compile_context The compile context to be used.
+     * @param[in]  input           The input tensor to convert. 3 lower dimensions represent a single input [width, height, IFM],
+     *                             while every optional dimension from 4 and above represent a batch of inputs. Data types supported: QASYMM8/QASYMM8_SIGNED/F16/F32
+     * @param[out] output          The output tensor. First 2 lower dimensions represent a transform of each 3D input,
+     *                             while every dimension above represents a batch. Data types supported: Same as @p input
+     * @param[in]  kernel_dims     The kernel dimensions (width and height).
+     * @param[in]  conv_info       Contains padding and stride information described in @ref PadStrideInfo.
+     * @param[in]  has_bias        In case biases are provided expands the matrix with 1.
+     * @param[in]  dilation        (Optional) Dilation, in elements, across x and y. Defaults to (1, 1).
+     * @param[in]  num_groups      (Optional) Number of groups when performing a grouped convolution. num_groups != 1 is only supported for NCHW data layout
+     */
+    void configure(CLCompileContext &compile_context, const ICLTensor *input, ICLTensor *output, const Size2D &kernel_dims, const PadStrideInfo &conv_info, bool has_bias,
+                   const Size2D &dilation   = Size2D(1U, 1U),
+                   unsigned int  num_groups = 1);
     /** Static function to check if given info will lead to a valid configuration of @ref CLIm2ColKernel
      *
      * @param[in] input       The input tensor to convert. 3 lower dimensions represent a single input [width, height, IFM],
diff --git a/arm_compute/core/CL/kernels/CLInstanceNormalizationLayerKernel.h b/arm_compute/core/CL/kernels/CLInstanceNormalizationLayerKernel.h
index 9982cc2..93490d8 100644
--- a/arm_compute/core/CL/kernels/CLInstanceNormalizationLayerKernel.h
+++ b/arm_compute/core/CL/kernels/CLInstanceNormalizationLayerKernel.h
@@ -58,6 +58,15 @@
      * @param[in]      info   Kernel meta-data descriptor
      */
     void configure(ICLTensor *input, ICLTensor *output, const InstanceNormalizationLayerKernelInfo &info);
+    /** Set the input and output tensors.
+     *
+     * @param[in]      compile_context The compile context to be used.
+     * @param[in, out] input           Source tensor. Data types supported: F16/F32. Data layout supported: NCHW, NHWC
+     *                                 In case of @p output tensor = nullptr this tensor will store the result of the normalization.
+     * @param[out]     output          Destination tensor. Data types and data layouts supported: same as @p input.
+     * @param[in]      info            Kernel meta-data descriptor
+     */
+    void configure(CLCompileContext &compile_context, ICLTensor *input, ICLTensor *output, const InstanceNormalizationLayerKernelInfo &info);
 
     /** Static function to check if given info will lead to a valid configuration of @ref CLInstanceNormalizationLayer.
      *
diff --git a/arm_compute/core/CL/kernels/CLIntegralImageKernel.h b/arm_compute/core/CL/kernels/CLIntegralImageKernel.h
index 42b0be3..8e06887 100644
--- a/arm_compute/core/CL/kernels/CLIntegralImageKernel.h
+++ b/arm_compute/core/CL/kernels/CLIntegralImageKernel.h
@@ -1,5 +1,5 @@
 /*
- * Copyright (c) 2016-2019 ARM Limited.
+ * Copyright (c) 2016-2020 ARM Limited.
  *
  * SPDX-License-Identifier: MIT
  *
@@ -41,6 +41,13 @@
      * @param[out] output Destination tensor, Data types supported: U32.
      */
     void configure(const ICLTensor *input, ICLTensor *output);
+    /** Initialise the kernel's input and output.
+     *
+     * @param[in]  compile_context The compile context to be used.
+     * @param[in]  input           An input tensor. Data types supported: U8
+     * @param[out] output          Destination tensor, Data types supported: U32.
+     */
+    void configure(CLCompileContext &compile_context, const ICLTensor *input, ICLTensor *output);
 };
 
 /** Interface to run the vertical pass of the integral image kernel. */
@@ -62,6 +69,12 @@
      * @param[in,out] in_out The input/output tensor. Data types supported: U32
      */
     void configure(ICLTensor *in_out);
+    /** Initialise the kernel's input and output.
+     *
+     * @param[in]     compile_context The compile context to be used.
+     * @param[in,out] in_out          The input/output tensor. Data types supported: U32
+     */
+    void configure(CLCompileContext &compile_context, ICLTensor *in_out);
 
     // Inherited methods overridden:
     void run(const Window &window, cl::CommandQueue &queue) override;
diff --git a/arm_compute/core/CL/kernels/CLL2NormalizeLayerKernel.h b/arm_compute/core/CL/kernels/CLL2NormalizeLayerKernel.h
index b6f1be1..e4b7af7 100644
--- a/arm_compute/core/CL/kernels/CLL2NormalizeLayerKernel.h
+++ b/arm_compute/core/CL/kernels/CLL2NormalizeLayerKernel.h
@@ -1,5 +1,5 @@
 /*
- * Copyright (c) 2017-2019 ARM Limited.
+ * Copyright (c) 2017-2020 ARM Limited.
  *
  * SPDX-License-Identifier: MIT
  *
@@ -59,6 +59,18 @@
      * @param[in]  epsilon Lower bound value for the normalization.
      */
     void configure(const ICLTensor *input, const ICLTensor *sum, ICLTensor *output, int axis, float epsilon);
+    /** Set the input and output tensors.
+     *
+     * @param[in]  compile_context The compile context to be used.
+     * @param[in]  input           Source tensor. Data types supported: F16/F32. Data layouts supported: NCHW/NHWC.
+     * @param[in]  sum             Sum values tensor. Data types supported: same as @p input.
+     *                             Sum will have the same number of dimensions as input.
+     * @param[out] output          Destination tensor. Data types and data layouts supported: Same as @p input.
+     *                             Output will have the same number of dimensions as input.
+     * @param[in]  axis            Axis along which to reduce. Negative values wrap around. Maximum supported actual reduction axis : 2
+     * @param[in]  epsilon         Lower bound value for the normalization.
+     */
+    void configure(CLCompileContext &compile_context, const ICLTensor *input, const ICLTensor *sum, ICLTensor *output, int axis, float epsilon);
 
     /** Static function to check if given info will lead to a valid configuration of @ref CLL2NormalizeLayerKernel.
      *
diff --git a/arm_compute/core/CL/kernels/CLLKTrackerKernel.h b/arm_compute/core/CL/kernels/CLLKTrackerKernel.h
index 1f24894..3e938c9 100644
--- a/arm_compute/core/CL/kernels/CLLKTrackerKernel.h
+++ b/arm_compute/core/CL/kernels/CLLKTrackerKernel.h
@@ -1,5 +1,5 @@
 /*
- * Copyright (c) 2017-2019 ARM Limited.
+ * Copyright (c) 2017-2020 ARM Limited.
  *
  * SPDX-License-Identifier: MIT
  *
@@ -87,6 +87,21 @@
     void configure(const ICLKeyPointArray *old_points, const ICLKeyPointArray *new_points_estimates,
                    ICLLKInternalKeypointArray *old_points_internal, ICLLKInternalKeypointArray *new_points_internal,
                    bool use_initial_estimate, size_t level, size_t num_levels, float pyramid_scale);
+    /** Initialise the kernel input and output
+     *
+     * @param[in]  compile_context      The compile context to be used.
+     * @param[in]  old_points           Pointer to the @ref ICLKeyPointArray storing old key points
+     * @param[in]  new_points_estimates Pointer to the @ref ICLKeyPointArray storing new estimates key points
+     * @param[out] old_points_internal  Pointer to the array of internal @ref CLLKInternalKeypoint old points
+     * @param[out] new_points_internal  Pointer to the array of internal @ref CLLKInternalKeypoint new points
+     * @param[in]  use_initial_estimate The flag to indicate whether the initial estimated position should be used
+     * @param[in]  level                The pyramid level
+     * @param[in]  num_levels           The number of pyramid levels
+     * @param[in]  pyramid_scale        Scale factor used for generating the pyramid
+     */
+    void configure(CLCompileContext &compile_context, const ICLKeyPointArray *old_points, const ICLKeyPointArray *new_points_estimates,
+                   ICLLKInternalKeypointArray *old_points_internal, ICLLKInternalKeypointArray *new_points_internal,
+                   bool use_initial_estimate, size_t level, size_t num_levels, float pyramid_scale);
 
     // Inherited methods overridden:
     void run(const Window &window, cl::CommandQueue &queue) override;
@@ -102,6 +117,13 @@
      * @param[out] new_points          Pointer to the @ref ICLKeyPointArray storing new key points
      */
     void configure(ICLLKInternalKeypointArray *new_points_internal, ICLKeyPointArray *new_points);
+    /** Initialise the kernel input and output
+     *
+     * @param[in]  compile_context     The compile context to be used.
+     * @param[in]  new_points_internal Pointer to the array of internal @ref CLLKInternalKeypoint new points
+     * @param[out] new_points          Pointer to the @ref ICLKeyPointArray storing new key points
+     */
+    void configure(CLCompileContext &compile_context, ICLLKInternalKeypointArray *new_points_internal, ICLKeyPointArray *new_points);
 
     // Inherited methods overridden:
     void run(const Window &window, cl::CommandQueue &queue) override;
@@ -137,6 +159,23 @@
                    ICLLKInternalKeypointArray *old_points_internal, ICLLKInternalKeypointArray *new_points_internal,
                    ICLCoefficientTableArray *coeff_table, ICLOldValArray *old_ival,
                    size_t window_dimension, size_t level);
+    /** Initialise the kernel input and output
+     *
+     * @param[in]      compile_context     The compile context to be used.
+     * @param[in]      old_input           Pointer to the input old tensor. Data types supported: U8
+     * @param[in]      old_scharr_gx       Pointer to the input scharr X tensor. Data types supported: S16
+     * @param[in]      old_scharr_gy       Pointer to the input scharr Y tensor. Data types supported: S16
+     * @param[in]      old_points_internal Pointer to the array of CLLKInternalKeypoint old points
+     * @param[in, out] new_points_internal Pointer to the array of CLLKInternalKeypoint new points
+     * @param[out]     coeff_table         Pointer to the array holding the Spatial Gradient coefficients
+     * @param[out]     old_ival            Pointer to the array holding internal values
+     * @param[in]      window_dimension    The size of the window on which to perform the algorithm
+     * @param[in]      level               The pyramid level
+     */
+    void configure(CLCompileContext &compile_context, const ICLTensor *old_input, const ICLTensor *old_scharr_gx, const ICLTensor *old_scharr_gy,
+                   ICLLKInternalKeypointArray *old_points_internal, ICLLKInternalKeypointArray *new_points_internal,
+                   ICLCoefficientTableArray *coeff_table, ICLOldValArray *old_ival,
+                   size_t window_dimension, size_t level);
 
     // Inherited methods overridden:
     void run(const Window &window, cl::CommandQueue &queue) override;
@@ -175,6 +214,21 @@
      */
     void configure(const ICLTensor *new_input, ICLLKInternalKeypointArray *new_points_internal, ICLCoefficientTableArray *coeff_table, ICLOldValArray *old_ival,
                    Termination termination, float epsilon, size_t num_iterations, size_t window_dimension, size_t level);
+    /** Initialise the kernel input and output
+     *
+     * @param[in]      compile_context     The compile context to be used.
+     * @param[in]      new_input           Pointer to the input new tensor. Data types supported: U8
+     * @param[in, out] new_points_internal Pointer to the array of CLLKInternalKeypoint for new points
+     * @param[in]      coeff_table         Pointer to the array holding the Spatial Gradient coefficients
+     * @param[in]      old_ival            Pointer to the array holding internal values
+     * @param[in]      termination         The criteria to terminate the search of each keypoint.
+     * @param[in]      epsilon             The error for terminating the algorithm
+     * @param[in]      num_iterations      The maximum number of iterations before terminating the algorithm
+     * @param[in]      window_dimension    The size of the window on which to perform the algorithm
+     * @param[in]      level               The pyramid level
+     */
+    void configure(CLCompileContext &compile_context, const ICLTensor *new_input, ICLLKInternalKeypointArray *new_points_internal, ICLCoefficientTableArray *coeff_table, ICLOldValArray *old_ival,
+                   Termination termination, float epsilon, size_t num_iterations, size_t window_dimension, size_t level);
 
     // Inherited methods overridden:
     void run(const Window &window, cl::CommandQueue &queue) override;
diff --git a/arm_compute/core/CL/kernels/CLLocallyConnectedMatrixMultiplyKernel.h b/arm_compute/core/CL/kernels/CLLocallyConnectedMatrixMultiplyKernel.h
index 2f5624a..757e3e4 100644
--- a/arm_compute/core/CL/kernels/CLLocallyConnectedMatrixMultiplyKernel.h
+++ b/arm_compute/core/CL/kernels/CLLocallyConnectedMatrixMultiplyKernel.h
@@ -1,5 +1,5 @@
 /*
- * Copyright (c) 2017-2019 ARM Limited.
+ * Copyright (c) 2017-2020 ARM Limited.
  *
  * SPDX-License-Identifier: MIT
  *
@@ -55,6 +55,14 @@
      * @param[out] output Output tensor to store the result. Data type supported: same as @p input0
      */
     void configure(const ICLTensor *input0, const ICLTensor *input1, ICLTensor *output);
+    /** Initialise the kernel's input, output and alpha
+     *
+     * @param[in]  compile_context The compile context to be used.
+     * @param[in]  input0          First input tensor. Data types supported: F32
+     * @param[in]  input1          Second input tensor. Data type supported: same as @p input0
+     * @param[out] output          Output tensor to store the result. Data type supported: same as @p input0
+     */
+    void configure(CLCompileContext &compile_context, const ICLTensor *input0, const ICLTensor *input1, ICLTensor *output);
     /** Static function to check if given info will lead to a valid configuration of @ref CLLocallyConnectedMatrixMultiplyKernel
      *
      * @param[in] input0 First input tensor info. Data types supported: F32
diff --git a/arm_compute/core/CL/kernels/CLMagnitudePhaseKernel.h b/arm_compute/core/CL/kernels/CLMagnitudePhaseKernel.h
index 75b63f9..390da49 100644
--- a/arm_compute/core/CL/kernels/CLMagnitudePhaseKernel.h
+++ b/arm_compute/core/CL/kernels/CLMagnitudePhaseKernel.h
@@ -1,5 +1,5 @@
 /*
- * Copyright (c) 2016-2019 ARM Limited.
+ * Copyright (c) 2016-2020 ARM Limited.
  *
  * SPDX-License-Identifier: MIT
  *
@@ -60,6 +60,20 @@
      */
     void configure(const ICLTensor *gx, const ICLTensor *gy, ICLTensor *magnitude, ICLTensor *phase,
                    MagnitudeType mag_type = MagnitudeType::L2NORM, PhaseType phase_type = PhaseType::SIGNED);
+    /** Initialise the kernel's input, output.
+     *
+     * @note At least one of output1 or output2 must be set.
+     *
+     * @param[in]  compile_context The compile context to be used.
+     * @param[in]  gx              The input gradient X tensor. Data types supported: S16.
+     * @param[in]  gy              The input gradient Y tensor. Data types supported: S16.
+     * @param[out] magnitude       (Optional) The output tensor - Magnitude. Data types supported: S16.
+     * @param[out] phase           (Optional) The output tensor - Phase. Data types supported: U8.
+     * @param[in]  mag_type        (Optional) Magnitude calculation type. Default: L2NORM.
+     * @param[in]  phase_type      (Optional) Phase calculation type. Default: SIGNED.
+     */
+    void configure(CLCompileContext &compile_context, const ICLTensor *gx, const ICLTensor *gy, ICLTensor *magnitude, ICLTensor *phase,
+                   MagnitudeType mag_type = MagnitudeType::L2NORM, PhaseType phase_type = PhaseType::SIGNED);
 
     // Inherited methods overridden:
     void run(const Window &window, cl::CommandQueue &queue) override;
diff --git a/arm_compute/core/CL/kernels/CLMeanStdDevKernel.h b/arm_compute/core/CL/kernels/CLMeanStdDevKernel.h
index 1f3129f..ed0213a 100644
--- a/arm_compute/core/CL/kernels/CLMeanStdDevKernel.h
+++ b/arm_compute/core/CL/kernels/CLMeanStdDevKernel.h
@@ -1,5 +1,5 @@
 /*
- * Copyright (c) 2016-2019 ARM Limited.
+ * Copyright (c) 2016-2020 ARM Limited.
  *
  * SPDX-License-Identifier: MIT
  *
@@ -59,6 +59,16 @@
      * @param[out] global_sum_squared (Optional if stddev is not set, required if stddev is set) Keeps global sum of squared pixel values (Buffer size: 1 cl_ulong).
      */
     void configure(const ICLImage *input, float *mean, cl::Buffer *global_sum, float *stddev = nullptr, cl::Buffer *global_sum_squared = nullptr);
+    /** Initialise the kernel's input and outputs.
+     *
+     * @param[in]  compile_context    The compile context to be used.
+     * @param[in]  input              Input image. Data types supported: U8.
+     * @param[out] mean               Input average pixel value.
+     * @param[out] global_sum         Keeps global sum of pixel values (Buffer size: 1 cl_ulong).
+     * @param[out] stddev             (Optional) Output standard deviation of pixel values.
+     * @param[out] global_sum_squared (Optional if stddev is not set, required if stddev is set) Keeps global sum of squared pixel values (Buffer size: 1 cl_ulong).
+     */
+    void configure(CLCompileContext &compile_context, const ICLImage *input, float *mean, cl::Buffer *global_sum, float *stddev = nullptr, cl::Buffer *global_sum_squared = nullptr);
     /** Static function to check if given info will lead to a valid configuration of @ref CLMeanStdDevKernel.
      *
      * @param[in] input              Input image info. Data types supported: U8.
diff --git a/arm_compute/core/CL/kernels/CLMeanStdDevNormalizationKernel.h b/arm_compute/core/CL/kernels/CLMeanStdDevNormalizationKernel.h
index ece0ec4..a21a6ee 100644
--- a/arm_compute/core/CL/kernels/CLMeanStdDevNormalizationKernel.h
+++ b/arm_compute/core/CL/kernels/CLMeanStdDevNormalizationKernel.h
@@ -1,5 +1,5 @@
 /*
- * Copyright (c) 2019 ARM Limited.
+ * Copyright (c) 2019-2020 ARM Limited.
  *
  * SPDX-License-Identifier: MIT
  *
@@ -56,6 +56,17 @@
      * @param[in]      epsilon (Optional) Small float to avoid division by zero in case of zero standard deviation. Defaults to 1e-8.
      */
     void configure(ICLTensor *input, ICLTensor *output = nullptr, float epsilon = 1e-8f);
+    /** Initialise the kernel's input and outputs.
+     *
+     * @note If the output tensor is a nullptr, the normalization will be performed in-place.
+     *
+     * @param[in]      compile_context The compile context to be used.
+     * @param[in, out] input           Source tensor with 2 dimensions. In case of @p output tensor = nullptr,
+     *                                 this tensor will store the result of the normalization. Data types supported: F16/F32.
+     * @param[out]     output          (Optional) Destination tensor. It can be nullptr in case of in-place computation. Data type supported: same as @p input
+     * @param[in]      epsilon         (Optional) Small float to avoid division by zero in case of zero standard deviation. Defaults to 1e-8.
+     */
+    void configure(CLCompileContext &compile_context, ICLTensor *input, ICLTensor *output = nullptr, float epsilon = 1e-8f);
     /** Static function to check if given info will lead to a valid configuration of @ref CLMeanStdDevNormalizationKernel
      *
      * @param[in] input   Source tensor info with 2 dimensions. In case of @p output tensor info = nullptr,
diff --git a/arm_compute/core/CL/kernels/CLMedian3x3Kernel.h b/arm_compute/core/CL/kernels/CLMedian3x3Kernel.h
index 7fe5116..df40fcf 100644
--- a/arm_compute/core/CL/kernels/CLMedian3x3Kernel.h
+++ b/arm_compute/core/CL/kernels/CLMedian3x3Kernel.h
@@ -1,5 +1,5 @@
 /*
- * Copyright (c) 2016-2019 ARM Limited.
+ * Copyright (c) 2016-2020 ARM Limited.
  *
  * SPDX-License-Identifier: MIT
  *
@@ -43,6 +43,14 @@
      * @param[in]  border_undefined True if the border mode is undefined. False if it's replicate or constant.
      */
     void configure(const ICLTensor *input, ICLTensor *output, bool border_undefined);
+    /** Initialise the kernel's input and output.
+     *
+     * @param[in]  compile_context  The compile context to be used.
+     * @param[in]  input            An input tensor. Data types supported: U8
+     * @param[out] output           The output tensor. Data types supported: U8.
+     * @param[in]  border_undefined True if the border mode is undefined. False if it's replicate or constant.
+     */
+    void configure(CLCompileContext &compile_context, const ICLTensor *input, ICLTensor *output, bool border_undefined);
 
     // Inherited methods overridden:
     BorderSize border_size() const override;
diff --git a/arm_compute/core/CL/kernels/CLMemsetKernel.h b/arm_compute/core/CL/kernels/CLMemsetKernel.h
index 3e1eadf..a2e61a1 100644
--- a/arm_compute/core/CL/kernels/CLMemsetKernel.h
+++ b/arm_compute/core/CL/kernels/CLMemsetKernel.h
@@ -56,6 +56,14 @@
      * @param[in]     window         Window to be used in case setting only part of a tensor. Default is nullptr.
      */
     void configure(ICLTensor *tensor, const PixelValue &constant_value, Window *window = nullptr);
+    /** Initialise the kernel's tensor and filling value
+     *
+     * @param[in]     compile_context The compile context to be used.
+     * @param[in,out] tensor          Input tensor to fill. Supported data types: All.
+     * @param[in]     constant_value  The value used to fill the planes of the tensor
+     * @param[in]     window          Window to be used in case setting only part of a tensor. Default is nullptr.
+     */
+    void configure(CLCompileContext &compile_context, ICLTensor *tensor, const PixelValue &constant_value, Window *window = nullptr);
     /** Static function to check if given info will lead to a valid configuration of @ref CLMemsetKernel
      *
      * @param[in] tensor         Source tensor info. Data types supported: All.
diff --git a/arm_compute/core/CL/kernels/CLMinMaxLayerKernel.h b/arm_compute/core/CL/kernels/CLMinMaxLayerKernel.h
index f24cebb..7a31d71 100644
--- a/arm_compute/core/CL/kernels/CLMinMaxLayerKernel.h
+++ b/arm_compute/core/CL/kernels/CLMinMaxLayerKernel.h
@@ -1,5 +1,5 @@
 /*
- * Copyright (c) 2017-2019 ARM Limited.
+ * Copyright (c) 2017-2020 ARM Limited.
  *
  * SPDX-License-Identifier: MIT
  *
@@ -52,6 +52,14 @@
      *                    The dimensions over the second must match the batched dimensions of the input tensor. Data types supported: F32.
      */
     void configure(const ICLTensor *input, ICLTensor *output);
+    /** Initialise the kernel's input and output.
+     *
+     * @param[in]  compile_context The compile context to be used.
+     * @param[in]  input           Input tensor with at least 3 dimensions. The dimensions over the third will be interpreted as batches.Data types supported: F32.
+     * @param[out] output          Output tensor with shape [2, batches, ...] which stores the minimum and maximum values for each 3D input tensor.
+     *                    The dimensions over the second must match the batched dimensions of the input tensor. Data types supported: F32.
+     */
+    void configure(CLCompileContext &compile_context, const ICLTensor *input, ICLTensor *output);
     /** Static function to check if given info will lead to a valid configuration of @ref CLMinMaxLayerKernel
      *
      * @param[in] input  Input tensor info.  Data types supported: F32.
diff --git a/arm_compute/core/CL/kernels/CLMinMaxLocationKernel.h b/arm_compute/core/CL/kernels/CLMinMaxLocationKernel.h
index 67b5b38..e57f758 100644
--- a/arm_compute/core/CL/kernels/CLMinMaxLocationKernel.h
+++ b/arm_compute/core/CL/kernels/CLMinMaxLocationKernel.h
@@ -1,5 +1,5 @@
 /*
- * Copyright (c) 2017-2019 ARM Limited.
+ * Copyright (c) 2017-2020 ARM Limited.
  *
  * SPDX-License-Identifier: MIT
  *
@@ -55,6 +55,13 @@
      * @param[out] min_max Buffer of 2 elements to store the min value at position 0 and the max value at position 1. Data type supported: S32 if input type is U8/S16, F32 if input type is F32.
      */
     void configure(const ICLImage *input, cl::Buffer *min_max);
+    /** Initialise the kernel's input and output.
+     *
+     * @param[in]  compile_context The compile context to be used.
+     * @param[in]  input           Input Image. Data types supported: U8/S16/F32.
+     * @param[out] min_max         Buffer of 2 elements to store the min value at position 0 and the max value at position 1. Data type supported: S32 if input type is U8/S16, F32 if input type is F32.
+     */
+    void configure(CLCompileContext &compile_context, const ICLImage *input, cl::Buffer *min_max);
 
     // Inherited methods overridden:
     void run(const Window &window, cl::CommandQueue &queue) override;
@@ -92,6 +99,19 @@
      */
     void configure(const ICLImage *input, cl::Buffer *min_max, cl::Buffer *min_max_count,
                    ICLCoordinates2DArray *min_loc = nullptr, ICLCoordinates2DArray *max_loc = nullptr);
+    /** Initialise the kernel's input and outputs.
+     *
+     * @note When locations of min and max occurrences are requested, the reported number of locations is limited to the given array size.
+     *
+     * @param[in]  compile_context The compile context to be used.
+     * @param[in]  input           Input image. Data types supported: U8/S16/F32.
+     * @param[out] min_max         Buffer of 2 elements to store the min value at position 0 and the max value at position 1. Data type supported: S32 if input type is U8/S16, F32 if input type is F32.
+     * @param[out] min_max_count   Buffer of 2 elements to store the min value occurrences at position 0 and the max value occurrences at position 1. Data type supported: S32
+     * @param[out] min_loc         (Optional) Array of Coordinates2D used to store minimum value locations.
+     * @param[out] max_loc         (Optional) Array of Coordinates2D used to store maximum value locations.
+     */
+    void configure(CLCompileContext &compile_context, const ICLImage *input, cl::Buffer *min_max, cl::Buffer *min_max_count,
+                   ICLCoordinates2DArray *min_loc = nullptr, ICLCoordinates2DArray *max_loc = nullptr);
 
     // Inherited methods overridden:
     void run(const Window &window, cl::CommandQueue &queue) override;
diff --git a/arm_compute/core/CL/kernels/CLNonLinearFilterKernel.h b/arm_compute/core/CL/kernels/CLNonLinearFilterKernel.h
index a6846b2..b255f0c 100644
--- a/arm_compute/core/CL/kernels/CLNonLinearFilterKernel.h
+++ b/arm_compute/core/CL/kernels/CLNonLinearFilterKernel.h
@@ -1,5 +1,5 @@
 /*
- * Copyright (c) 2017-2019 ARM Limited.
+ * Copyright (c) 2017-2020 ARM Limited.
  *
  * SPDX-License-Identifier: MIT
  *
@@ -52,6 +52,20 @@
     void configure(const ICLTensor *input, ICLTensor *output, NonLinearFilterFunction function,
                    unsigned int mask_size, MatrixPattern pattern, const uint8_t *mask,
                    bool border_undefined);
+    /** Set the source, destination and border mode of the kernel
+     *
+     * @param[in]  compile_context  The compile context to be used.
+     * @param[in]  input            Source tensor. Data types supported: U8
+     * @param[out] output           Destination tensor. Data types supported: U8
+     * @param[in]  function         Non linear function to perform
+     * @param[in]  mask_size        Mask size. Supported sizes: 3, 5
+     * @param[in]  pattern          Mask pattern
+     * @param[in]  mask             The given mask. Will be used only if pattern is specified to PATTERN_OTHER
+     * @param[in]  border_undefined True if the border mode is undefined. False if it's replicate or constant.
+     */
+    void configure(CLCompileContext &compile_context, const ICLTensor *input, ICLTensor *output, NonLinearFilterFunction function,
+                   unsigned int mask_size, MatrixPattern pattern, const uint8_t *mask,
+                   bool border_undefined);
 
     // Inherited methods overridden:
     BorderSize border_size() const override;
diff --git a/arm_compute/core/CL/kernels/CLNonMaximaSuppression3x3Kernel.h b/arm_compute/core/CL/kernels/CLNonMaximaSuppression3x3Kernel.h
index dd36a29..084c77b 100644
--- a/arm_compute/core/CL/kernels/CLNonMaximaSuppression3x3Kernel.h
+++ b/arm_compute/core/CL/kernels/CLNonMaximaSuppression3x3Kernel.h
@@ -1,5 +1,5 @@
 /*
- * Copyright (c) 2016-2019 ARM Limited.
+ * Copyright (c) 2016-2020 ARM Limited.
  *
  * SPDX-License-Identifier: MIT
  *
@@ -44,6 +44,14 @@
      * @param[in]  border_undefined True if the border mode is undefined. False if it's replicate or constant.
      */
     void configure(const ICLTensor *input, ICLTensor *output, bool border_undefined);
+    /** Initialise the kernel's sources, destinations and border mode.
+     *
+     * @param[in]  compile_context  The compile context to be used.
+     * @param[in]  input            Source tensor. Data types supported: U8, F32. (Must be the same as the output tensor)
+     * @param[out] output           Destination tensor. Data types supported: U8, F32. (Must be the same as the input tensor)
+     * @param[in]  border_undefined True if the border mode is undefined. False if it's replicate or constant.
+     */
+    void configure(CLCompileContext &compile_context, const ICLTensor *input, ICLTensor *output, bool border_undefined);
 
     // Inherited methods overridden:
     BorderSize border_size() const override;
diff --git a/arm_compute/core/CL/kernels/CLNormalizationLayerKernel.h b/arm_compute/core/CL/kernels/CLNormalizationLayerKernel.h
index 43e219a..350b504 100644
--- a/arm_compute/core/CL/kernels/CLNormalizationLayerKernel.h
+++ b/arm_compute/core/CL/kernels/CLNormalizationLayerKernel.h
@@ -1,5 +1,5 @@
 /*
- * Copyright (c) 2017-2019 ARM Limited.
+ * Copyright (c) 2017-2020 ARM Limited.
  *
  * SPDX-License-Identifier: MIT
  *
@@ -54,6 +54,16 @@
      * @param[in]  norm_info Normalization layer information like the normalization type, normalization size and other parameters.
      */
     void configure(const ICLTensor *input, ICLTensor *output, NormalizationLayerInfo norm_info);
+    /** Set the input and output tensors.
+     *
+     * @param[in]  compile_context The compile context to be used.
+     * @param[in]  input           Source tensor. 3 lower dims represent a single input with dimensions [width, height, IFM],
+     *                             and an optional 4th dimension for batch of inputs. Data types supported: F16/F32. Data layouts supported: NCHW/NHWC.
+     * @param[out] output          Destination tensor. Output will have the same number of dimensions as input. Data types supported: same as @p input.
+     *                             Data layouts supported: same as @p input.
+     * @param[in]  norm_info       Normalization layer information like the normalization type, normalization size and other parameters.
+     */
+    void configure(CLCompileContext &compile_context, const ICLTensor *input, ICLTensor *output, NormalizationLayerInfo norm_info);
     /** Static function to check if given info will lead to a valid configuration of @ref CLNormalizationLayerKernel
      *
      * @param[in] input     Source tensor. 3 lower dims represent a single input with dimensions [width, height, IFM],
diff --git a/arm_compute/core/CL/kernels/CLNormalizePlanarYUVLayerKernel.h b/arm_compute/core/CL/kernels/CLNormalizePlanarYUVLayerKernel.h
index 4334882..addd394 100644
--- a/arm_compute/core/CL/kernels/CLNormalizePlanarYUVLayerKernel.h
+++ b/arm_compute/core/CL/kernels/CLNormalizePlanarYUVLayerKernel.h
@@ -57,6 +57,17 @@
      *                    Data types supported: same as @p input
      */
     void configure(const ICLTensor *input, ICLTensor *output, const ICLTensor *mean, const ICLTensor *std);
+    /** Set the input and output tensors.
+     *
+     * @param[in]  compile_context The compile context to be used.
+     * @param[in]  input           Source tensor. 3 lower dimensions represent a single input with dimensions [width, height, channels].
+     *                             Data types supported: QASYMM8/QASYMM8_SIGNED/F16/F32.
+     * @param[out] output          Destination tensor. Data type supported: same as @p input
+     * @param[in]  mean            Mean values tensor. 1 dimension with size equal to the number of input channels. Data types supported: same as @p input
+     * @param[in]  std             Standard deviation values tensor. 1 dimension with size equal to the number of input channels.
+     *                             Data types supported: same as @p input
+     */
+    void configure(CLCompileContext &compile_context, const ICLTensor *input, ICLTensor *output, const ICLTensor *mean, const ICLTensor *std);
     /** Static function to check if given info will lead to a valid configuration of @ref CLNormalizePlanarYUVLayerKernel
      *
      * @param[in]  input  Source tensor info. 3 lower dimensions represent a single input with dimensions [width, height, channels].
diff --git a/arm_compute/core/CL/kernels/CLPadLayerKernel.h b/arm_compute/core/CL/kernels/CLPadLayerKernel.h
index 6865ae6..09f7208 100644
--- a/arm_compute/core/CL/kernels/CLPadLayerKernel.h
+++ b/arm_compute/core/CL/kernels/CLPadLayerKernel.h
@@ -58,6 +58,19 @@
      *                            or reflect the input, either including the border values (SYMMETRIC) or not (REFLECT).
      */
     void configure(const ICLTensor *input, ICLTensor *output, const PaddingList &padding, PixelValue constant_value = PixelValue(), PaddingMode mode = PaddingMode::CONSTANT);
+    /** Set the input and output tensor.
+     *
+     * @param[in]  compile_context The compile context to be used.
+     * @param[in]  input           Source tensor. Data types supported: All.
+     * @param[out] output          Output tensor. Data type supported: same as @p input
+     * @param[in]  padding         The padding for each spatial dimension of the input tensor. The pair padding[i]
+     *                             specifies the front and the end padding in the i-th dimension.
+     * @param[in]  constant_value  (Optional) Constant value to be used for the padding.
+     * @param[in]  mode            (Optional) Controls whether the padding should be filled with @p constant_value using CONSTANT,
+     *                             or reflect the input, either including the border values (SYMMETRIC) or not (REFLECT).
+     */
+    void configure(CLCompileContext &compile_context, const ICLTensor *input, ICLTensor *output, const PaddingList &padding, PixelValue constant_value = PixelValue(),
+                   PaddingMode mode = PaddingMode::CONSTANT);
     /** Static function to check if given info will lead to a valid configuration of @ref CLPadLayerKernel
      *
      * @param[in] input          Source tensor info. Data types supported: All.
diff --git a/arm_compute/core/CL/kernels/CLPermuteKernel.h b/arm_compute/core/CL/kernels/CLPermuteKernel.h
index bc51f10..6414edb 100644
--- a/arm_compute/core/CL/kernels/CLPermuteKernel.h
+++ b/arm_compute/core/CL/kernels/CLPermuteKernel.h
@@ -56,6 +56,16 @@
      * @param[in] perm   Permutation vector
      */
     void configure(const ICLTensor *input, ICLTensor *output, const PermutationVector &perm);
+    /** Set the input and output of the kernel.
+     *
+     * @note Arbitrary permutation vectors are supported with rank not greater than 4
+     *
+     * @param[in] compile_context The compile context to be used.
+     * @param[in] input           The input tensor to permute. Data types supported: All.
+     * @param[in] output          The output tensor. Data types supported: Same as @p input
+     * @param[in] perm            Permutation vector
+     */
+    void configure(CLCompileContext &compile_context, const ICLTensor *input, ICLTensor *output, const PermutationVector &perm);
     /** Static function to check if given info will lead to a valid configuration of @ref CLPermuteKernel
      *
      * @note Arbitrary permutation vectors are supported with rank not greater than 4
diff --git a/arm_compute/core/CL/kernels/CLPixelWiseMultiplicationKernel.h b/arm_compute/core/CL/kernels/CLPixelWiseMultiplicationKernel.h
index 2a54a4b..a9cfcc5 100644
--- a/arm_compute/core/CL/kernels/CLPixelWiseMultiplicationKernel.h
+++ b/arm_compute/core/CL/kernels/CLPixelWiseMultiplicationKernel.h
@@ -67,6 +67,20 @@
      */
     void configure(const ICLTensor *input1, const ICLTensor *input2, ICLTensor *output, float scale,
                    ConvertPolicy overflow_policy, RoundingPolicy rounding_policy, const ActivationLayerInfo &act_info = ActivationLayerInfo());
+    /** Initialise the kernel's input, output and border mode.
+     *
+     * @param[in]  compile_context The compile context to be used.
+     * @param[in]  input1          An input tensor. Data types supported: U8/QASYMM8/QASYMM8_SIGNED/S16/QSYMM16/F16/F32.
+     * @param[in]  input2          An input tensor. Data types supported: same as @p input1.
+     * @param[out] output          The output tensor, Data types supported: same as @p input1. Note: U8 requires both inputs to be U8.
+     * @param[in]  scale           Scale to apply after multiplication.
+     *                             Scale must be positive and its value must be either 1/255 or 1/2^n where n is between 0 and 15.
+     * @param[in]  overflow_policy Overflow policy. Supported overflow policies: Wrap, Saturate
+     * @param[in]  rounding_policy Rounding policy. Supported rounding modes: to zero, to nearest even.
+     * @param[in]  act_info        (Optional) Activation layer information in case of a fused activation.
+     */
+    void configure(CLCompileContext &compile_context, const ICLTensor *input1, const ICLTensor *input2, ICLTensor *output, float scale,
+                   ConvertPolicy overflow_policy, RoundingPolicy rounding_policy, const ActivationLayerInfo &act_info = ActivationLayerInfo());
     /** Static function to check if given info will lead to a valid configuration of @ref CLPixelWiseMultiplicationKernel
      *
      * @param[in] input1          An input tensor info. Data types supported: U8/QASYMM8/QASYMM8_SIGNED/S16/QSYMM16/F16/F32.
@@ -123,6 +137,15 @@
      * @param[in]  act_info (Optional) Activation layer information in case of a fused activation.
      */
     void configure(const ICLTensor *input1, const ICLTensor *input2, ICLTensor *output, const ActivationLayerInfo &act_info = ActivationLayerInfo());
+    /** Initialise the kernel's input, output and border mode.
+     *
+     * @param[in]  compile_context The compile context to be used.
+     * @param[in]  input1          An input tensor. Data types supported: F32. Number of channels supported: 2.
+     * @param[in]  input2          An input tensor. Data types supported: same as @p input1. Number of channels supported: same as @p input1.
+     * @param[out] output          The output tensor, Data types supported: same as @p input1. Number of channels supported: same as @p input1.
+     * @param[in]  act_info        (Optional) Activation layer information in case of a fused activation.
+     */
+    void configure(CLCompileContext &compile_context, const ICLTensor *input1, const ICLTensor *input2, ICLTensor *output, const ActivationLayerInfo &act_info = ActivationLayerInfo());
     /** Static function to check if given info will lead to a valid configuration of @ref CLComplexPixelWiseMultiplicationKernel
      *
      * @param[in] input1   An input tensor info. Data types supported: F32. Number of channels supported: 2.
diff --git a/arm_compute/core/CL/kernels/CLPoolingLayerKernel.h b/arm_compute/core/CL/kernels/CLPoolingLayerKernel.h
index fdd10f3..4ab6955 100644
--- a/arm_compute/core/CL/kernels/CLPoolingLayerKernel.h
+++ b/arm_compute/core/CL/kernels/CLPoolingLayerKernel.h
@@ -58,6 +58,16 @@
      * @param[out] indices   (optional) The indices of the maximal values. Data type supported: U32.
      */
     void configure(const ICLTensor *input, ICLTensor *output, const PoolingLayerInfo &pool_info, ICLTensor *indices = nullptr);
+    /** Set the input and output tensors.
+     *
+     *
+     * @param[in]  compile_context The compile context to be used.
+     * @param[in]  input           Source tensor. Data types supported: QASYMM8/QASYMM8_SIGNED/F16/F32.
+     * @param[out] output          Destination tensor. Data types supported: Same as @p input.
+     * @param[in]  pool_info       Contains pooling operation information described in @ref PoolingLayerInfo.
+     * @param[out] indices         (optional) The indices of the maximal values. Data type supported: U32.
+     */
+    void configure(CLCompileContext &compile_context, const ICLTensor *input, ICLTensor *output, const PoolingLayerInfo &pool_info, ICLTensor *indices = nullptr);
     /** Static function to check if given info will lead to a valid configuration of @ref CLPoolingLayerKernel
      *
      * @param[in] input     Source tensor info. Data types supported: QASYMM8/QASYMM8_SIGNED/F16/F32.
diff --git a/arm_compute/core/CL/kernels/CLPriorBoxLayerKernel.h b/arm_compute/core/CL/kernels/CLPriorBoxLayerKernel.h
index 8376934..89fd656 100644
--- a/arm_compute/core/CL/kernels/CLPriorBoxLayerKernel.h
+++ b/arm_compute/core/CL/kernels/CLPriorBoxLayerKernel.h
@@ -1,5 +1,5 @@
 /*
- * Copyright (c) 2018-2019 ARM Limited.
+ * Copyright (c) 2018-2020 ARM Limited.
  *
  * SPDX-License-Identifier: MIT
  *
@@ -58,6 +58,19 @@
      * @param[in]  aspect_ratios Aspect ratio values
      */
     void configure(const ICLTensor *input1, const ICLTensor *input2, ICLTensor *output, const PriorBoxLayerInfo &info, cl::Buffer *min, cl::Buffer *max, cl::Buffer *aspect_ratios);
+    /** Set the input and output tensors.
+     *
+     * @param[in]  compile_context The compile context to be used.
+     * @param[in]  input1          First source tensor. Data types supported: F32. Data layouts supported: NCHW/NHWC.
+     * @param[in]  input2          Second source tensor. Data types and layouts supported: same as @p input1
+     * @param[out] output          Destination tensor. Output dimensions are [W * H * num_priors * 4, 2]. Data types and layouts supported: same as @p input1
+     * @param[in]  info            Prior box layer info.
+     * @param[in]  min             Minimum prior box values
+     * @param[in]  max             Maximum prior box values
+     * @param[in]  aspect_ratios   Aspect ratio values
+     */
+    void configure(CLCompileContext &compile_context, const ICLTensor *input1, const ICLTensor *input2, ICLTensor *output, const PriorBoxLayerInfo &info, cl::Buffer *min, cl::Buffer *max,
+                   cl::Buffer *aspect_ratios);
     /** Static function to check if given info will lead to a valid configuration of @ref CLPriorBoxLayerKernel
      *
      * @param[in] input1 First source tensor info. Data types supported: F32. Data layouts supported: NCHW/NHWC.
diff --git a/arm_compute/core/CL/kernels/CLQuantizationLayerKernel.h b/arm_compute/core/CL/kernels/CLQuantizationLayerKernel.h
index 07c93d3..a651529 100644
--- a/arm_compute/core/CL/kernels/CLQuantizationLayerKernel.h
+++ b/arm_compute/core/CL/kernels/CLQuantizationLayerKernel.h
@@ -57,6 +57,15 @@
      * @note Output auto initialization is not supported by this kernel
      */
     void configure(const ICLTensor *input, ICLTensor *output);
+    /** Set the input, output.
+     *
+     * @param[in]  compile_context The compile context to be used.
+     * @param[in]  input           Source tensor. Data types supported: QASYMM8/QASYMM8_SIGNED/F32/F16.
+     * @param[out] output          Destination tensor with the same dimensions of input. Data types supported: QASYMM8/QASYMM8_SIGNED/QASYMM16.
+     *
+     * @note Output auto initialization is not supported by this kernel
+     */
+    void configure(CLCompileContext &compile_context, const ICLTensor *input, ICLTensor *output);
     /** Static function to check if given info will lead to a valid configuration of @ref CLQuantizationLayerKernel
      *
      * @param[in] input  Input tensor info. Data types supported: QASYMM8/QASYMM8_SIGNED/F32/F16.
diff --git a/arm_compute/core/CL/kernels/CLROIAlignLayerKernel.h b/arm_compute/core/CL/kernels/CLROIAlignLayerKernel.h
index 8dc7e4d..8f4485a 100644
--- a/arm_compute/core/CL/kernels/CLROIAlignLayerKernel.h
+++ b/arm_compute/core/CL/kernels/CLROIAlignLayerKernel.h
@@ -64,6 +64,22 @@
      * @note The fourth dimension of @p output tensor must be the same as the number of elements in @p rois array.
      */
     void configure(const ICLTensor *input, const ICLTensor *rois, ICLTensor *output, const ROIPoolingLayerInfo &pool_info);
+    /** Set the input and output tensors.
+     *
+     * @param[in]  compile_context The compile context to be used.
+     * @param[in]  input           Source tensor. Data types supported: QASYMM8/QASYMM8_SIGNED/F16/F32.
+     * @param[in]  rois            ROIs tensor, it is a 2D tensor of size [5, N] (where N is the number of ROIs) containing top left and bottom right corner
+     *                             as coordinate of an image and batch_id of ROI [ batch_id, x1, y1, x2, y2 ].
+     *                             Data types supported: QASYMM16 with scale of 0.125 and 0 offset if @p input is QASYMM8/QASYMM8_SIGNED, otherwise same as @p input
+     * @param[out] output          Destination tensor. Data types supported: Same as @p input.
+     * @param[in]  pool_info       Contains pooling operation information described in @ref ROIPoolingLayerInfo.
+     *
+     * @note The x and y dimensions of @p output tensor must be the same as @p pool_info 's pooled
+     * width and pooled height.
+     * @note The z dimensions of @p output tensor and @p input tensor must be the same.
+     * @note The fourth dimension of @p output tensor must be the same as the number of elements in @p rois array.
+     */
+    void configure(CLCompileContext &compile_context, const ICLTensor *input, const ICLTensor *rois, ICLTensor *output, const ROIPoolingLayerInfo &pool_info);
     /** Static function to check if given info will lead to a valid configuration of @ref CLROIAlignLayerKernel
      *
      * @param[in] input     Source tensor info. Data types supported: QASYMM8/QASYMM8_SIGNED/F16/F32.
diff --git a/arm_compute/core/CL/kernels/CLROIPoolingLayerKernel.h b/arm_compute/core/CL/kernels/CLROIPoolingLayerKernel.h
index 2936877..8ba1b35 100644
--- a/arm_compute/core/CL/kernels/CLROIPoolingLayerKernel.h
+++ b/arm_compute/core/CL/kernels/CLROIPoolingLayerKernel.h
@@ -1,5 +1,5 @@
 /*
- * Copyright (c) 2017-2019 ARM Limited.
+ * Copyright (c) 2017-2020 ARM Limited.
  *
  * SPDX-License-Identifier: MIT
  *
@@ -63,6 +63,21 @@
      * @note The fourth dimension of @p output tensor must be the same as the number of elements in @p rois array.
      */
     void configure(const ICLTensor *input, const ICLTensor *rois, ICLTensor *output, const ROIPoolingLayerInfo &pool_info);
+    /** Set the input and output tensors.
+     *
+     * @param[in]  compile_context The compile context to be used.
+     * @param[in]  input           Source tensor. Data types supported: F16/F32.
+     * @param[in]  rois            ROIs tensor, it is a 2D tensor of size [5, N] (where N is the number of ROIs) containing top left and bottom right corner
+     *                             as coordinate of an image and batch_id of ROI [ batch_id, x1, y1, x2, y2 ]. Data types supported: U16
+     * @param[out] output          Destination tensor. Data types supported: Same as @p input.
+     * @param[in]  pool_info       Contains pooling operation information described in @ref ROIPoolingLayerInfo.
+     *
+     * @note The x and y dimensions of @p output tensor must be the same as @p pool_info 's pooled
+     * width and pooled height.
+     * @note The z dimensions of @p output tensor and @p input tensor must be the same.
+     * @note The fourth dimension of @p output tensor must be the same as the number of elements in @p rois array.
+     */
+    void configure(CLCompileContext &compile_context, const ICLTensor *input, const ICLTensor *rois, ICLTensor *output, const ROIPoolingLayerInfo &pool_info);
 
     // Inherited methods overridden:
     void run(const Window &window, cl::CommandQueue &queue) override;
diff --git a/arm_compute/core/CL/kernels/CLRangeKernel.h b/arm_compute/core/CL/kernels/CLRangeKernel.h
index 27dd813..5cc4a22 100644
--- a/arm_compute/core/CL/kernels/CLRangeKernel.h
+++ b/arm_compute/core/CL/kernels/CLRangeKernel.h
@@ -1,5 +1,5 @@
 /*
- * Copyright (c) 2018-2019 ARM Limited.
+ * Copyright (c) 2018-2020 ARM Limited.
  *
  * SPDX-License-Identifier: MIT
  *
@@ -59,6 +59,15 @@
      * @param[in]  step   The gap between each pair of values in the sequence.
      */
     void configure(ICLTensor *output, float start, float end, float step);
+    /** Initialize the kernel's output tensor, start, end and step of the sequence.
+     *
+     * @param[in]  compile_context The compile context to be used.
+     * @param[out] output          Output tensor. Data types supported: U8/S8/QASYMM8/U16/S16/U32/S32/F16/F32.
+     * @param[in]  start           The starting value of the sequence.
+     * @param[in]  end             The ending (not including) value of the sequence.
+     * @param[in]  step            The gap between each pair of values in the sequence.
+     */
+    void configure(CLCompileContext &compile_context, ICLTensor *output, float start, float end, float step);
     /** Static function to check if given info will lead to a valid configuration of @ref CLRangeKernel
      *
      * @param[in] output Output tensor info. Data types supported: U8/S8/QASYMM8/U16/S16/U32/S32/F16/F32.
diff --git a/arm_compute/core/CL/kernels/CLReductionOperationKernel.h b/arm_compute/core/CL/kernels/CLReductionOperationKernel.h
index 07ebd89..bdab58b 100644
--- a/arm_compute/core/CL/kernels/CLReductionOperationKernel.h
+++ b/arm_compute/core/CL/kernels/CLReductionOperationKernel.h
@@ -59,6 +59,17 @@
      * @param[in]  width  (Optional)  In case of x-axis we also need to provide the width of the input image.
      */
     void configure(const ICLTensor *input, ICLTensor *output, unsigned int axis, ReductionOperation op, unsigned int width = 0);
+    /** Set the input and output tensors.
+     *
+     * @param[in]  compile_context The compile context to be used.
+     * @param[in]  input           Source tensor. Data types supported: QASYMM8/QASYMM8_SIGNED/S32/F16/F32.
+     * @param[out] output          Destination tensor. Data types and data layouts supported: Same as @p input.
+     *                             Output will have the same number of dimensions as input.
+     * @param[in]  axis            Axis along which to reduce. Supported reduction axis : 0,1,2,3
+     * @param[in]  op              Reduction operation to perform. Operations supported: MEAN_SUM, PROD, SUM_SQUARE, SUM, MIN, MAX
+     * @param[in]  width           (Optional)  In case of x-axis we also need to provide the width of the input image.
+     */
+    void configure(CLCompileContext &compile_context, const ICLTensor *input, ICLTensor *output, unsigned int axis, ReductionOperation op, unsigned int width = 0);
 
     /** Static function to check if given info will lead to a valid configuration of @ref CLReductionOperationKernel.
      *
diff --git a/arm_compute/core/CL/kernels/CLRemapKernel.h b/arm_compute/core/CL/kernels/CLRemapKernel.h
index ce094bc..14f4b2d 100644
--- a/arm_compute/core/CL/kernels/CLRemapKernel.h
+++ b/arm_compute/core/CL/kernels/CLRemapKernel.h
@@ -1,5 +1,5 @@
 /*
- * Copyright (c) 2017-2019 ARM Limited.
+ * Copyright (c) 2017-2020 ARM Limited.
  *
  * SPDX-License-Identifier: MIT
  *
@@ -55,6 +55,17 @@
      * @param[in]  border_undefined True if the border mode is undefined. False if it's replicate or constant.
      */
     void configure(const ICLTensor *input, const ICLTensor *map_x, const ICLTensor *map_y, ICLTensor *output, InterpolationPolicy policy, bool border_undefined);
+    /** Initialize the kernel's input, output and border mode.
+     *
+     * @param[in]  compile_context  The compile context to be used.
+     * @param[in]  input            Source tensor. Data types supported: U8.
+     * @param[in]  map_x            Map for X coordinates. Data types supported: F32.
+     * @param[in]  map_y            Map for Y coordinates. Data types supported: F32.
+     * @param[out] output           Destination tensor. Data types supported: U8. All but the lowest two dimensions must be the same size as in the input tensor, i.e. remapping is only performed within the XY-plane.
+     * @param[in]  policy           The interpolation type.
+     * @param[in]  border_undefined True if the border mode is undefined. False if it's replicate or constant.
+     */
+    void configure(CLCompileContext &compile_context, const ICLTensor *input, const ICLTensor *map_x, const ICLTensor *map_y, ICLTensor *output, InterpolationPolicy policy, bool border_undefined);
 
     // Inherited methods overridden:
     void run(const Window &window, cl::CommandQueue &queue) override;
diff --git a/arm_compute/core/CL/kernels/CLReorgLayerKernel.h b/arm_compute/core/CL/kernels/CLReorgLayerKernel.h
index c1bbb0a..65304c1 100644
--- a/arm_compute/core/CL/kernels/CLReorgLayerKernel.h
+++ b/arm_compute/core/CL/kernels/CLReorgLayerKernel.h
@@ -55,6 +55,17 @@
      *                    It defines the spatial distance between 2 consecutive pixels in the x and y direction
      */
     void configure(const ICLTensor *input, ICLTensor *output, int32_t stride);
+    /** Initialize the kernel's input, output.
+     *
+     * @param[in]  compile_context The compile context to be used.
+     * @param[in]  input           Source tensor. Data types supported: U8/S8/QASYMM8/QASYMM8_SIGNED/U16/S16/F16/U32/S32/F32.
+     * @param[out] output          Destination tensor with tensor shape:
+     *                             [width_input / stride, height_input / stride, channels_input * stride * stride, batch_size]. This means the output has
+     *                             the same number of input elements. Data types supported: same as @p input.
+     * @param[in]  stride          Stride value to use for reorganizing the values in the output tensor.
+     *                             It defines the spatial distance between 2 consecutive pixels in the x and y direction
+     */
+    void configure(CLCompileContext &compile_context, const ICLTensor *input, ICLTensor *output, int32_t stride);
     /** Static function to check if given info will lead to a valid configuration of @ref CLReorgLayerKernel
      *
      * @param[in] input  Source tensor. Data types supported: All.
diff --git a/arm_compute/core/CL/kernels/CLReshapeLayerKernel.h b/arm_compute/core/CL/kernels/CLReshapeLayerKernel.h
index 77aedf3..f9588e8 100644
--- a/arm_compute/core/CL/kernels/CLReshapeLayerKernel.h
+++ b/arm_compute/core/CL/kernels/CLReshapeLayerKernel.h
@@ -53,6 +53,13 @@
      * @param[out] output Destination tensor. Data type supported: Same as @p input
      */
     void configure(const ICLTensor *input, ICLTensor *output);
+    /** Set the input and output of the kernel
+     *
+     * @param[in]  compile_context The compile context to be used.
+     * @param[in]  input           Source tensor. Data type supported: All.
+     * @param[out] output          Destination tensor. Data type supported: Same as @p input
+     */
+    void configure(CLCompileContext &compile_context, const ICLTensor *input, ICLTensor *output);
 
     /** Static function to check if given info will lead to a valid configuration of @ref CLReshapeLayerKernel
      *
diff --git a/arm_compute/core/CL/kernels/CLReverseKernel.h b/arm_compute/core/CL/kernels/CLReverseKernel.h
index c8d10f7..b1547cf 100644
--- a/arm_compute/core/CL/kernels/CLReverseKernel.h
+++ b/arm_compute/core/CL/kernels/CLReverseKernel.h
@@ -53,6 +53,14 @@
      * @param[in]  axis   Axis tensor. Contains the indices of the dimensions to reverse. Data type supported: U32
      */
     void configure(const ICLTensor *input, ICLTensor *output, const ICLTensor *axis);
+    /** Initialise the kernel's inputis and output
+     *
+     * @param[in]  compile_context The compile context to be used.
+     * @param[in]  input           Input tensor. Data types supported: All.
+     * @param[out] output          Output tensor. Data type supported: Same as @p input
+     * @param[in]  axis            Axis tensor. Contains the indices of the dimensions to reverse. Data type supported: U32
+     */
+    void configure(CLCompileContext &compile_context, const ICLTensor *input, ICLTensor *output, const ICLTensor *axis);
 
     /** Static function to check if given info will lead to a valid configuration of @ref CLReverseKernel
      *
diff --git a/arm_compute/core/CL/kernels/CLScaleKernel.h b/arm_compute/core/CL/kernels/CLScaleKernel.h
index f93286b..02dfb3e 100644
--- a/arm_compute/core/CL/kernels/CLScaleKernel.h
+++ b/arm_compute/core/CL/kernels/CLScaleKernel.h
@@ -46,6 +46,19 @@
      * @param[in]  align_corners   (Optional) Align corners of input and output, only affecting bilinear policy with TOP_LEFT sampling policy. Defaults to false.
      */
     void configure(const ICLTensor *input, ICLTensor *output, InterpolationPolicy policy, BorderMode border_mode, SamplingPolicy sampling_policy = SamplingPolicy::CENTER, bool align_corners = false);
+    /** Initialise the kernel's inputs, output and interpolation policy
+     *
+     * @param[in]  compile_context The compile context to be used.
+     * @param[in]  input           Source tensor. Data types supported: U8/QASYMM8/QASYMM8_SIGNED/S16/F16/F32
+     * @param[out] output          Destination tensor. Data types supported: Same as @p input
+     *                             All but the lowest two dimensions must be the same size as in the input tensor, i.e. scaling is only performed within the XY-plane.
+     * @param[in]  policy          Interpolation type to use
+     * @param[in]  border_mode     Selected border mode.
+     * @param[in]  sampling_policy (Optional) Sampling policy used by the interpolation. Defaults to @ref SamplingPolicy::CENTER
+     * @param[in]  align_corners   (Optional) Align corners of input and output, only affecting bilinear policy with TOP_LEFT sampling policy. Defaults to false.
+     */
+    void configure(CLCompileContext &compile_context, const ICLTensor *input, ICLTensor *output, InterpolationPolicy policy, BorderMode border_mode,
+                   SamplingPolicy sampling_policy = SamplingPolicy::CENTER, bool align_corners = false);
 
     /** Static function to check if given info will lead to a valid configuration of @ref CLScaleKernel
      *
diff --git a/arm_compute/core/CL/kernels/CLScharr3x3Kernel.h b/arm_compute/core/CL/kernels/CLScharr3x3Kernel.h
index 3d4e4eb..1cdb667 100644
--- a/arm_compute/core/CL/kernels/CLScharr3x3Kernel.h
+++ b/arm_compute/core/CL/kernels/CLScharr3x3Kernel.h
@@ -1,5 +1,5 @@
 /*
- * Copyright (c) 2016-2019 ARM Limited.
+ * Copyright (c) 2016-2020 ARM Limited.
  *
  * SPDX-License-Identifier: MIT
  *
@@ -70,6 +70,17 @@
      * @param[in]  border_undefined True if the border mode is undefined. False if it's replicate or constant.
      */
     void configure(const ICLTensor *input, ICLTensor *output_x, ICLTensor *output_y, bool border_undefined);
+    /** Initialise the kernel's source, destination and border.
+     *
+     * @note At least one of output_x or output_y must be set.
+     *
+     * @param[in]  compile_context  The compile context to be used.
+     * @param[in]  input            Source tensor. Data types supported: U8.
+     * @param[out] output_x         (Optional) Destination tensor for the X gradient, Data types supported: S16.
+     * @param[out] output_y         (Optional) Destination tensor for the Y gradient, Data types supported: S16.
+     * @param[in]  border_undefined True if the border mode is undefined. False if it's replicate or constant.
+     */
+    void configure(CLCompileContext &compile_context, const ICLTensor *input, ICLTensor *output_x, ICLTensor *output_y, bool border_undefined);
 
     // Inherited methods overridden:
     void run(const Window &window, cl::CommandQueue &queue) override;
diff --git a/arm_compute/core/CL/kernels/CLSelectKernel.h b/arm_compute/core/CL/kernels/CLSelectKernel.h
index be43add..02f4ccc 100644
--- a/arm_compute/core/CL/kernels/CLSelectKernel.h
+++ b/arm_compute/core/CL/kernels/CLSelectKernel.h
@@ -60,6 +60,15 @@
      * @param[in]  output Output tensor. Data types supported: Same as @p x.
      */
     void configure(const ICLTensor *c, const ICLTensor *x, const ICLTensor *y, ICLTensor *output);
+    /** Initialise the kernel's inputs and output.
+     *
+     * @param[in]  compile_context The compile context to be used.
+     * @param[in]  c               Condition input tensor. Data types supported: U8.
+     * @param[in]  x               First input tensor. Data types supported: All.
+     * @param[out] y               Second input tensor. Data types supported: Same as @p x
+     * @param[in]  output          Output tensor. Data types supported: Same as @p x.
+     */
+    void configure(CLCompileContext &compile_context, const ICLTensor *c, const ICLTensor *x, const ICLTensor *y, ICLTensor *output);
     /** Static function to check if given info will lead to a valid configuration of @ref CLSelectKernel
      *
      * @param[in] c      Condition input tensor. Data types supported: U8.
diff --git a/arm_compute/core/CL/kernels/CLSobel3x3Kernel.h b/arm_compute/core/CL/kernels/CLSobel3x3Kernel.h
index 74d8346..3970c07 100644
--- a/arm_compute/core/CL/kernels/CLSobel3x3Kernel.h
+++ b/arm_compute/core/CL/kernels/CLSobel3x3Kernel.h
@@ -1,5 +1,5 @@
 /*
- * Copyright (c) 2016-2019 ARM Limited.
+ * Copyright (c) 2016-2020 ARM Limited.
  *
  * SPDX-License-Identifier: MIT
  *
@@ -56,6 +56,17 @@
      * @param[in]  border_undefined True if the border mode is undefined. False if it's replicate or constant.
      */
     void configure(const ICLTensor *input, ICLTensor *output_x, ICLTensor *output_y, bool border_undefined);
+    /** Initialise the kernel's source, destination and border.
+     *
+     * @note At least one of output_x or output_y must be set.
+     *
+     * @param[in]  compile_context  The compile context to be used.
+     * @param[in]  input            Source tensor. Data types supported: U8.
+     * @param[out] output_x         (Optional) Destination tensor for the X gradient, Data types supported: S16.
+     * @param[out] output_y         (Optional) Destination tensor for the Y gradient, Data types supported: S16.
+     * @param[in]  border_undefined True if the border mode is undefined. False if it's replicate or constant.
+     */
+    void configure(CLCompileContext &compile_context, const ICLTensor *input, ICLTensor *output_x, ICLTensor *output_y, bool border_undefined);
 
     // Inherited methods overridden:
     void run(const Window &window, cl::CommandQueue &queue) override;
diff --git a/arm_compute/core/CL/kernels/CLSobel5x5Kernel.h b/arm_compute/core/CL/kernels/CLSobel5x5Kernel.h
index 20a69ea..0aff209 100644
--- a/arm_compute/core/CL/kernels/CLSobel5x5Kernel.h
+++ b/arm_compute/core/CL/kernels/CLSobel5x5Kernel.h
@@ -1,5 +1,5 @@
 /*
- * Copyright (c) 2016-2019 ARM Limited.
+ * Copyright (c) 2016-2020 ARM Limited.
  *
  * SPDX-License-Identifier: MIT
  *
@@ -57,6 +57,17 @@
      * @param[in]  border_undefined True if the border mode is undefined. False if it's replicate or constant.
      */
     void configure(const ICLTensor *input, ICLTensor *output_x, ICLTensor *output_y, bool border_undefined);
+    /** Initialise the kernel's source, destination and border.
+     *
+     * @note At least one of output_x or output_y must be set.
+     *
+     * @param[in]  compile_context  The compile context to be used.
+     * @param[in]  input            Source tensor. Data types supported: U8.
+     * @param[out] output_x         (Optional) Destination tensor for the X gradient, Data types supported: S16.
+     * @param[out] output_y         (Optional) Destination tensor for the Y gradient, Data types supported: S16.
+     * @param[in]  border_undefined True if the border mode is undefined. False if it's replicate or constant.
+     */
+    void configure(CLCompileContext &compile_context, const ICLTensor *input, ICLTensor *output_x, ICLTensor *output_y, bool border_undefined);
 
     // Inherited methods overridden:
     void run(const Window &window, cl::CommandQueue &queue) override;
@@ -99,6 +110,18 @@
      * @param[in]  border_undefined True if the border mode is undefined. False if it's replicate or constant.
      */
     void configure(const ICLTensor *input_x, const ICLTensor *input_y, ICLTensor *output_x, ICLTensor *output_y, bool border_undefined);
+    /** Initialise the kernel's source, destination and border.
+     *
+     * @note At least one of output_x or output_y must be set and the corresponding input.
+     *
+     * @param[in]  compile_context  The compile context to be used.
+     * @param[in]  input_x          (Optional) Input for X (X output of horizontal pass). Data types supported: S16.
+     * @param[in]  input_y          (Optional) Input for Y (Y output of horizontal pass). Data types supported: S16.
+     * @param[out] output_x         (Optional) Destination tensor for the X gradient, Data types supported: S16.
+     * @param[out] output_y         (Optional) Destination tensor for the Y gradient, Data types supported: S16.
+     * @param[in]  border_undefined True if the border mode is undefined. False if it's replicate or constant.
+     */
+    void configure(CLCompileContext &compile_context, const ICLTensor *input_x, const ICLTensor *input_y, ICLTensor *output_x, ICLTensor *output_y, bool border_undefined);
 
     // Inherited methods overridden:
     void run(const Window &window, cl::CommandQueue &queue) override;
diff --git a/arm_compute/core/CL/kernels/CLSobel7x7Kernel.h b/arm_compute/core/CL/kernels/CLSobel7x7Kernel.h
index 3c224f7..31809b1 100644
--- a/arm_compute/core/CL/kernels/CLSobel7x7Kernel.h
+++ b/arm_compute/core/CL/kernels/CLSobel7x7Kernel.h
@@ -1,5 +1,5 @@
 /*
- * Copyright (c) 2016-2019 ARM Limited.
+ * Copyright (c) 2016-2020 ARM Limited.
  *
  * SPDX-License-Identifier: MIT
  *
@@ -57,6 +57,17 @@
      * @param[in]  border_undefined True if the border mode is undefined. False if it's replicate or constant.
      */
     void configure(const ICLTensor *input, ICLTensor *output_x, ICLTensor *output_y, bool border_undefined);
+    /** Initialise the kernel's source, destination and border.
+     *
+     * @note At least one of output_x or output_y must be set.
+     *
+     * @param[in]  compile_context  The compile context to be used.
+     * @param[in]  input            Source tensor. Data types supported: U8.
+     * @param[out] output_x         (Optional) Destination tensor for the X gradient, Data types supported: S32.
+     * @param[out] output_y         (Optional) Destination tensor for the Y gradient, Data types supported: S32.
+     * @param[in]  border_undefined True if the border mode is undefined. False if it's replicate or constant.
+     */
+    void configure(CLCompileContext &compile_context, const ICLTensor *input, ICLTensor *output_x, ICLTensor *output_y, bool border_undefined);
 
     // Inherited methods overridden:
     void run(const Window &window, cl::CommandQueue &queue) override;
@@ -99,6 +110,18 @@
      * @param[in]  border_undefined True if the border mode is undefined. False if it's replicate or constant.
      */
     void configure(const ICLTensor *input_x, const ICLTensor *input_y, ICLTensor *output_x, ICLTensor *output_y, bool border_undefined);
+    /** Initialise the kernel's source, destination and border.
+     *
+     * @note At least one of output_x or output_y must be set and the corresponding input.
+     *
+     * @param[in]  compile_context  The compile context to be used.
+     * @param[in]  input_x          (Optional) Input for X (X output of horizontal pass). Data types supported: S32.
+     * @param[in]  input_y          (Optional) Input for Y (Y output of horizontal pass). Data types supported: S32.
+     * @param[out] output_x         (Optional) Destination tensor for the X gradient, Data types supported: S32.
+     * @param[out] output_y         (Optional) Destination tensor for the Y gradient, Data types supported: S32.
+     * @param[in]  border_undefined True if the border mode is undefined. False if it's replicate or constant.
+     */
+    void configure(CLCompileContext &compile_context, const ICLTensor *input_x, const ICLTensor *input_y, ICLTensor *output_x, ICLTensor *output_y, bool border_undefined);
 
     // Inherited methods overridden:
     void run(const Window &window, cl::CommandQueue &queue) override;
diff --git a/arm_compute/core/CL/kernels/CLSoftmaxLayerKernel.h b/arm_compute/core/CL/kernels/CLSoftmaxLayerKernel.h
index f64739a..800d909 100644
--- a/arm_compute/core/CL/kernels/CLSoftmaxLayerKernel.h
+++ b/arm_compute/core/CL/kernels/CLSoftmaxLayerKernel.h
@@ -1,5 +1,5 @@
 /*
- * Copyright (c) 2017-2019 ARM Limited.
+ * Copyright (c) 2017-2020 ARM Limited.
  *
  * SPDX-License-Identifier: MIT
  *
@@ -43,6 +43,13 @@
      * @param[out] output Destination tensor. Data types supported: same as @p input
      */
     void configure(const ICLTensor *input, ICLTensor *output);
+    /** Set the input and output tensors.
+     *
+     * @param[in]  compile_context The compile context to be used.
+     * @param[in]  input           Source tensor. Data types supported: QASYMM8/F16/F32
+     * @param[out] output          Destination tensor. Data types supported: same as @p input
+     */
+    void configure(CLCompileContext &compile_context, const ICLTensor *input, ICLTensor *output);
     /** Static function to check if given info will lead to a valid configuration of @ref CLLogits1DMaxKernel
      *
      * @param[in] input  Source tensor. Data types supported: QASYMM8/F16/F32
@@ -76,6 +83,16 @@
      * @param[in]  beta   (Optional) A scaling factor for the exponent. Defaults to 1.0
      */
     void configure(const ICLTensor *input, const ICLTensor *max, ICLTensor *output, ICLTensor *sum, float beta = 1.0f);
+    /** Set the input and output tensors.
+     *
+     * @param[in]  compile_context The compile context to be used.
+     * @param[in]  input           Source tensor. Data types supported: QASYMM8/F16/F32
+     * @param[in]  max             Max values tensor. Data types supported: same as @p input
+     * @param[out] output          Destination tensor. Data types supported: S32 for QASYMM8 @p input, or same as @p input
+     * @param[out] sum             Sum of 1D logits tensor. Data types supported: S32 for QASYMM8 @p input, or same as @p input
+     * @param[in]  beta            (Optional) A scaling factor for the exponent. Defaults to 1.0
+     */
+    void configure(CLCompileContext &compile_context, const ICLTensor *input, const ICLTensor *max, ICLTensor *output, ICLTensor *sum, float beta = 1.0f);
     /** Static function to check if given info will lead to a valid configuration of @ref CLLogits1DShiftExpSumKernel
      *
      * @param[in] input  Source tensor. Data types supported: QASYMM8/F16/F32
@@ -124,6 +141,16 @@
      * @param[in]     info   Contains information consumed by kernels for softmax described in @ref SoftmaxKernelInfo.
      */
     void configure(const ICLTensor *input, ICLTensor *max, ICLTensor *output, ICLTensor *sum, const SoftmaxKernelInfo &info);
+    /** Set the input and output tensors.
+     *
+     * @param[in]     compile_context The compile context to be used.
+     * @param[in]     input           Source tensor. Data types supported: F16/F32
+     * @param[in,out] max             Max values tensor. Data types supported: same as @p input
+     * @param[out]    output          Destination tensor. Data types supported: same as @p input
+     * @param[out]    sum             Sum of 1D logits tensor. Data types supported: same as @p input
+     * @param[in]     info            Contains information consumed by kernels for softmax described in @ref SoftmaxKernelInfo.
+     */
+    void configure(CLCompileContext &compile_context, const ICLTensor *input, ICLTensor *max, ICLTensor *output, ICLTensor *sum, const SoftmaxKernelInfo &info);
     /** Static function to check if given info will lead to a valid configuration of @ref CLLogits1DMaxShiftExpSumKernel
      *
      * @param[in] input  Source tensor. Data types supported: F16/F32
@@ -182,6 +209,15 @@
      * @param[in]  info   Contains information consumed by kernels for softmax described in @ref SoftmaxKernelInfo.
      */
     void configure(const ICLTensor *input, const ICLTensor *sum, ICLTensor *output, const SoftmaxKernelInfo &info);
+    /** Set the input and output tensors.
+     *
+     * @param[in]  compile_context The compile context to be used.
+     * @param[in]  input           Source tensor. Data types supported: S32/F16/F32
+     * @param[in]  sum             Sum tensor. Dimensions should be dim(input)-1. Data types supported: same as @p input
+     * @param[out] output          Destination tensor. Data types supported: QASYMM8 for S32 @p input, or same as @p input
+     * @param[in]  info            Contains information consumed by kernels for softmax described in @ref SoftmaxKernelInfo.
+     */
+    void configure(CLCompileContext &compile_context, const ICLTensor *input, const ICLTensor *sum, ICLTensor *output, const SoftmaxKernelInfo &info);
     /** Static function to check if given info will lead to a valid configuration of @ref CLLogits1DNormKernel
      *
      * @param[in] input  Source tensor. Data types supported: S32/F16/F32
diff --git a/arm_compute/core/CL/kernels/CLSpaceToBatchLayerKernel.h b/arm_compute/core/CL/kernels/CLSpaceToBatchLayerKernel.h
index 6295430..34f0b66 100644
--- a/arm_compute/core/CL/kernels/CLSpaceToBatchLayerKernel.h
+++ b/arm_compute/core/CL/kernels/CLSpaceToBatchLayerKernel.h
@@ -55,6 +55,15 @@
      * @param[out] output      Tensor output. Data types supported: same as @p input
      */
     void configure(const ICLTensor *input, const ICLTensor *block_shape, const ICLTensor *paddings, ICLTensor *output);
+    /** Initialise the kernel's inputs and output.
+     *
+     * @param[in]  compile_context The compile context to be used.
+     * @param[in]  input           Tensor input. Supported tensor rank: 4. Data types supported: All.
+     * @param[in]  block_shape     1-D tensor with shape [M]. Data types supported: S32
+     * @param[in]  paddings        2-D tensor with shape [2, M]. Data types supported: S32
+     * @param[out] output          Tensor output. Data types supported: same as @p input
+     */
+    void configure(CLCompileContext &compile_context, const ICLTensor *input, const ICLTensor *block_shape, const ICLTensor *paddings, ICLTensor *output);
     /** Initialise the kernel's input and output. (Static block shape and paddings)
      *
      * @param[in]  input         Tensor input. Supported tensor rank: 4. Data types supported: All.
@@ -65,6 +74,17 @@
      * @param[out] output        Tensor output. Data types supported: same as @p input
      */
     void configure(const ICLTensor *input, const int block_shape_x, const int block_shape_y, const Size2D &padding_left, const Size2D &padding_right, ICLTensor *output);
+    /** Initialise the kernel's input and output. (Static block shape and paddings)
+     *
+     * @param[in]  compile_context The compile context to be used.
+     * @param[in]  input           Tensor input. Supported tensor rank: 4. Data types supported: All.
+     * @param[in]  block_shape_x   Block shape x value.
+     * @param[in]  block_shape_y   Block shape y value.
+     * @param[in]  padding_left    The left padding of the output tensor.
+     * @param[in]  padding_right   The right padding of the output tensor.
+     * @param[out] output          Tensor output. Data types supported: same as @p input
+     */
+    void configure(CLCompileContext &compile_context, const ICLTensor *input, const int block_shape_x, const int block_shape_y, const Size2D &padding_left, const Size2D &padding_right, ICLTensor *output);
     /** Static function to check if given info will lead to a valid configuration of @ref CLSpaceToBatchLayerKernel
      *
      * @param[in] input       Tensor input. Supported tensor rank: 4. Data types supported: All.
diff --git a/arm_compute/core/CL/kernels/CLSpaceToDepthLayerKernel.h b/arm_compute/core/CL/kernels/CLSpaceToDepthLayerKernel.h
index 085c337..3f20f66 100644
--- a/arm_compute/core/CL/kernels/CLSpaceToDepthLayerKernel.h
+++ b/arm_compute/core/CL/kernels/CLSpaceToDepthLayerKernel.h
@@ -54,6 +54,14 @@
      * @param[in]  block_shape Block shape value.
      */
     void configure(const ICLTensor *input, ICLTensor *output, int32_t block_shape);
+    /** Initialise the kernel's inputs and output.
+     *
+     * @param[in]  compile_context The compile context to be used.
+     * @param[in]  input           Tensor input. Supported tensor rank: 4. Data types supported: All.
+     * @param[out] output          Tensor output. Data types supported: same as @p input
+     * @param[in]  block_shape     Block shape value.
+     */
+    void configure(CLCompileContext &compile_context, const ICLTensor *input, ICLTensor *output, int32_t block_shape);
     /** Static function to check if given info will lead to a valid configuration of @ref CLSpaceToDepthLayerKernel.
      *
      * @param[in] input       Tensor input info. Supported tensor rank: 4. Data types supported: All.
diff --git a/arm_compute/core/CL/kernels/CLStackLayerKernel.h b/arm_compute/core/CL/kernels/CLStackLayerKernel.h
index 073c896..19925c2 100644
--- a/arm_compute/core/CL/kernels/CLStackLayerKernel.h
+++ b/arm_compute/core/CL/kernels/CLStackLayerKernel.h
@@ -61,6 +61,20 @@
      *
      */
     void configure(const ICLTensor *input, unsigned int axis, unsigned int idx_input, unsigned int num_tensors, ICLTensor *output);
+    /** Initialise the kernel's inputs and output
+     *
+     * @note Supported input tensor rank: up to 4
+     *
+     * @param[in]  compile_context The compile context to be used.
+     * @param[in]  input           Input tensor. Data types supported: All.
+     * @param[in]  axis            The dimension to stack the tensors along. It must be smaller than the number of input dimensions.
+     * @param[in]  idx_input       Index of the input tensor in the list of tensors to stack.
+     *                             All tensors in the list must have the same shape
+     * @param[in]  num_tensors     Number of tensors to stack
+     * @param[out] output          Output tensor. Data types supported: Same as @p input.
+     *
+     */
+    void configure(CLCompileContext &compile_context, const ICLTensor *input, unsigned int axis, unsigned int idx_input, unsigned int num_tensors, ICLTensor *output);
     /** Static function to check if given info will lead to a valid configuration of @ref CLStackLayerKernel
      *
      * @note Supported input tensor rank: up to 4
diff --git a/arm_compute/core/CL/kernels/CLStridedSliceKernel.h b/arm_compute/core/CL/kernels/CLStridedSliceKernel.h
index 3bcabaf..2e66882 100644
--- a/arm_compute/core/CL/kernels/CLStridedSliceKernel.h
+++ b/arm_compute/core/CL/kernels/CLStridedSliceKernel.h
@@ -67,6 +67,24 @@
     void configure(const ICLTensor *input, ICLTensor *output,
                    const Coordinates &starts, const Coordinates &ends, const BiStrides &strides,
                    int32_t begin_mask, int32_t end_mask, int32_t shrink_axis_mask);
+    /** Configure kernel
+     *
+     * @note Supported tensor rank: up to 4
+     *
+     * @param[in]  compile_context  The compile context to be used.
+     * @param[in]  input            Source tensor. Data type supported: All.
+     * @param[out] output           Destination tensor. Data type supported: Same as @p input
+     * @param[in]  starts           The starts of the dimensions of the input tensor to be sliced. The length must be of rank(input).
+     * @param[in]  ends             The ends of the dimensions of the input tensor to be sliced. The length must be of rank(input).
+     * @param[in]  strides          The strides of the dimensions of the input tensor to be sliced. The length must be of rank(input).
+     * @param[in]  begin_mask       If the ith bit of begin_mask is set, starts[i] is ignored and the fullest possible range in that dimension is used instead.
+     * @param[in]  end_mask         If the ith bit of end_mask is set, ends[i] is ignored and the fullest possible range in that dimension is used instead.
+     * @param[in]  shrink_axis_mask If the ith bit of shrink_axis_mask is set, it implies that the ith specification shrinks the dimensionality by 1.
+     *                              A slice of size 1 starting from starts[i] in the dimension must be preserved.
+     */
+    void configure(CLCompileContext &compile_context, const ICLTensor *input, ICLTensor *output,
+                   const Coordinates &starts, const Coordinates &ends, const BiStrides &strides,
+                   int32_t begin_mask, int32_t end_mask, int32_t shrink_axis_mask);
 
     /** Static function to check if given info will lead to a valid configuration of @ref CLStridedSliceKernel
      *
diff --git a/arm_compute/core/CL/kernels/CLTableLookupKernel.h b/arm_compute/core/CL/kernels/CLTableLookupKernel.h
index 67d9cde..9bbaf26 100644
--- a/arm_compute/core/CL/kernels/CLTableLookupKernel.h
+++ b/arm_compute/core/CL/kernels/CLTableLookupKernel.h
@@ -1,5 +1,5 @@
 /*
- * Copyright (c) 2016-2019 ARM Limited.
+ * Copyright (c) 2016-2020 ARM Limited.
  *
  * SPDX-License-Identifier: MIT
  *
@@ -42,6 +42,14 @@
      * @param[out] output The output tensor. Data types supported: U8, S16.
      */
     void configure(const ICLTensor *input, const ICLLut *lut, ICLTensor *output);
+    /** Initialise the kernel's input, lut and output.
+     *
+     * @param[in]  compile_context The compile context to be used.
+     * @param[in]  input           An input tensor. Data types supported: U8, S16.
+     * @param[in]  lut             The input LUT. Data types supported: U8, S16.
+     * @param[out] output          The output tensor. Data types supported: U8, S16.
+     */
+    void configure(CLCompileContext &compile_context, const ICLTensor *input, const ICLLut *lut, ICLTensor *output);
 };
 } // namespace arm_compute
 #endif /* ARM_COMPUTE_CLTABLELOOKUPKERNEL_H */
diff --git a/arm_compute/core/CL/kernels/CLThresholdKernel.h b/arm_compute/core/CL/kernels/CLThresholdKernel.h
index 3523e36..79e9f01 100644
--- a/arm_compute/core/CL/kernels/CLThresholdKernel.h
+++ b/arm_compute/core/CL/kernels/CLThresholdKernel.h
@@ -1,5 +1,5 @@
 /*
- * Copyright (c) 2016-2019 ARM Limited.
+ * Copyright (c) 2016-2020 ARM Limited.
  *
  * SPDX-License-Identifier: MIT
  *
@@ -51,6 +51,19 @@
      */
     void configure(const ICLTensor *input, ICLTensor *output, uint8_t threshold,
                    uint8_t false_value, uint8_t true_value, ThresholdType type, uint8_t upper);
+    /**Initialise the kernel's input, output and threshold parameters.
+     *
+     * @param[in]  compile_context The compile context to be used.
+     * @param[in]  input           An input tensor. Data types supported: U8
+     * @param[out] output          The output tensor. Data types supported: U8.
+     * @param[in]  threshold       Threshold. When the threshold type is RANGE, this is used as the lower threshold.
+     * @param[in]  false_value     value to set when the condition is not respected.
+     * @param[in]  true_value      value to set when the condition is respected.
+     * @param[in]  type            Thresholding type. Either RANGE or BINARY.
+     * @param[in]  upper           Upper threshold. Only used when the thresholding type is RANGE.
+     */
+    void configure(CLCompileContext &compile_context, const ICLTensor *input, ICLTensor *output, uint8_t threshold,
+                   uint8_t false_value, uint8_t true_value, ThresholdType type, uint8_t upper);
 };
 } // namespace arm_compute
 #endif /*ARM_COMPUTE_NETHRESHOLDKERNEL_H */
diff --git a/arm_compute/core/CL/kernels/CLTileKernel.h b/arm_compute/core/CL/kernels/CLTileKernel.h
index 2b0c430..1c9186c 100644
--- a/arm_compute/core/CL/kernels/CLTileKernel.h
+++ b/arm_compute/core/CL/kernels/CLTileKernel.h
@@ -55,6 +55,16 @@
      *
      */
     void configure(const ICLTensor *input, ICLTensor *output, const Multiples &multiples);
+    /** Set the source, destination of the kernel
+     *
+     * @param[in]  compile_context The compile context to be used.
+     * @param[in]  input           Source tensor. Data type supported: All.
+     * @param[in]  multiples       Contains the number of times the input tensor should be replicated on the given dimension.
+     *                             Cannot have more than 4 elements (tiling in dimensions greater than 4 is not supported).
+     * @param[out] output          Destination tensor. Same as @p input
+     *
+     */
+    void configure(CLCompileContext &compile_context, const ICLTensor *input, ICLTensor *output, const Multiples &multiples);
     /** Static function to check if given info will lead to a valid configuration of @ref CLTileKernel
      *
      * @param[in] input     Source tensor info. Data type supported: All.
diff --git a/arm_compute/core/CL/kernels/CLTransposeKernel.h b/arm_compute/core/CL/kernels/CLTransposeKernel.h
index 0adebde..37bd716 100644
--- a/arm_compute/core/CL/kernels/CLTransposeKernel.h
+++ b/arm_compute/core/CL/kernels/CLTransposeKernel.h
@@ -44,6 +44,13 @@
      * @param[out] output Output tensor. Data type supported: Same as @p input
      */
     void configure(const ICLTensor *input, ICLTensor *output);
+    /** Initialise the kernel's input and output.
+     *
+     * @param[in]  compile_context The compile context to be used.
+     * @param[in]  input           Input tensor. Data types supported: All.
+     * @param[out] output          Output tensor. Data type supported: Same as @p input
+     */
+    void configure(CLCompileContext &compile_context, const ICLTensor *input, ICLTensor *output);
     /** Static function to check if given info will lead to a valid configuration of @ref CLTransposeKernel
      *
      * @param[in] input  Input tensor. Data types supported: All.
diff --git a/arm_compute/core/CL/kernels/CLUpsampleLayerKernel.h b/arm_compute/core/CL/kernels/CLUpsampleLayerKernel.h
index 6f632aa..556e548 100644
--- a/arm_compute/core/CL/kernels/CLUpsampleLayerKernel.h
+++ b/arm_compute/core/CL/kernels/CLUpsampleLayerKernel.h
@@ -55,6 +55,15 @@
      * @param[in]  upsampling_policy Defines the policy to fill the intermediate pixels.
      */
     void configure(const ICLTensor *input, ICLTensor *output, const Size2D &info, const InterpolationPolicy upsampling_policy);
+    /** Initialise the kernel's input and output.
+     *
+     * @param[in]  compile_context   The compile context to be used.
+     * @param[in]  input             Source tensor. Data types supported: QASYMM8/QASYMM8_SIGNED/F16/F32.
+     * @param[out] output            Destination tensor. Data types supported: same as @p input.
+     * @param[in]  info              Contains stride information described in @ref Size2D.
+     * @param[in]  upsampling_policy Defines the policy to fill the intermediate pixels.
+     */
+    void configure(CLCompileContext &compile_context, const ICLTensor *input, ICLTensor *output, const Size2D &info, const InterpolationPolicy upsampling_policy);
     /** Static function to check if given info will lead to a valid configuration of @ref CLUpsampleLayerKernel
      *
      * @param[in] input             Source tensor info. Data types supported: QASYMM8/QASYMM8_SIGNED/F16/F32.
diff --git a/arm_compute/core/CL/kernels/CLWarpAffineKernel.h b/arm_compute/core/CL/kernels/CLWarpAffineKernel.h
index e4d0be6..bd26705 100644
--- a/arm_compute/core/CL/kernels/CLWarpAffineKernel.h
+++ b/arm_compute/core/CL/kernels/CLWarpAffineKernel.h
@@ -1,5 +1,5 @@
 /*
- * Copyright (c) 2016-2019 ARM Limited.
+ * Copyright (c) 2016-2020 ARM Limited.
  *
  * SPDX-License-Identifier: MIT
  *
@@ -44,6 +44,16 @@
      * @param[in]  policy The interpolation type.
      */
     void configure(const ICLTensor *input, ICLTensor *output, const std::array<float, 9> &matrix, InterpolationPolicy policy);
+    /** Initialize the function's source, destination, interpolation policy and border_mode.
+     *
+     * @param[in]  compile_context The compile context to be used.
+     * @param[in]  input           Source tensor. Data types supported: U8.
+     * @param[out] output          Destination tensor, Data types supported: U8.
+     * @param[in]  matrix          The perspective matrix. Must be 2x3 of type float
+     *                             The matrix argument requires 9 values, the last 3 values are ignored.
+     * @param[in]  policy          The interpolation type.
+     */
+    void configure(CLCompileContext &compile_context, const ICLTensor *input, ICLTensor *output, const std::array<float, 9> &matrix, InterpolationPolicy policy);
 
     // Inherited methods overridden:
     BorderSize border_size() const override;
diff --git a/arm_compute/core/CL/kernels/CLWarpPerspectiveKernel.h b/arm_compute/core/CL/kernels/CLWarpPerspectiveKernel.h
index cf6cb4c..4f4ff34 100644
--- a/arm_compute/core/CL/kernels/CLWarpPerspectiveKernel.h
+++ b/arm_compute/core/CL/kernels/CLWarpPerspectiveKernel.h
@@ -1,5 +1,5 @@
 /*
- * Copyright (c) 2016-2019 ARM Limited.
+ * Copyright (c) 2016-2020 ARM Limited.
  *
  * SPDX-License-Identifier: MIT
  *
@@ -42,6 +42,15 @@
      * @param[in]  policy The interpolation type.
      */
     void configure(const ICLTensor *input, ICLTensor *output, const std::array<float, 9> &matrix, InterpolationPolicy policy);
+    /** Initialize the function's source, destination, interpolation policy and border_mode.
+     *
+     * @param[in]  compile_context The compile context to be used.
+     * @param[in]  input           Source tensor. Data types supported: U8.
+     * @param[out] output          Destination tensor, Data types supported: U8.
+     * @param[in]  matrix          The perspective matrix. Must be 3x3 of type float.
+     * @param[in]  policy          The interpolation type.
+     */
+    void configure(CLCompileContext &compile_context, const ICLTensor *input, ICLTensor *output, const std::array<float, 9> &matrix, InterpolationPolicy policy);
 
     // Inherited methods overridden:
     BorderSize border_size() const override;
diff --git a/arm_compute/core/CL/kernels/CLWeightsReshapeKernel.h b/arm_compute/core/CL/kernels/CLWeightsReshapeKernel.h
index 3e29fea..f09eea9 100644
--- a/arm_compute/core/CL/kernels/CLWeightsReshapeKernel.h
+++ b/arm_compute/core/CL/kernels/CLWeightsReshapeKernel.h
@@ -1,5 +1,5 @@
 /*
- * Copyright (c) 2017-2019 ARM Limited.
+ * Copyright (c) 2017-2020 ARM Limited.
  *
  * SPDX-License-Identifier: MIT
  *
@@ -79,6 +79,20 @@
      *                        Number of groups greater than one are only supported for NCHW data layout, and the number of weights must be a multiple of it.
      */
     void configure(const ICLTensor *input, const ICLTensor *biases, ICLTensor *output, unsigned int num_groups = 1);
+    /** Set the input and output of the kernel.
+     *
+     * @param[in]  compile_context The compile context to be used.
+     * @param[in]  input           The input tensor to convert. Weights are 4D tensor with dimensions [kernel_x, kernel_y, IFM, OFM] if shared,
+     *                             and 5D tensor with dimensions [kernel_x, kernel_y, IFM, OFM,  num_patches] if unshared. Data types supported: All
+     * @param[in]  biases          The shared biases tensor to append.  Bias is 1D tensor with dimensions [OFM] if shared and 2D tensor with
+     *                             dimensions [OFM, num_patches] if unshared. Data types supported: F16/F32, for quantized types this must be nullptr.
+     *                             @warning Appending biases to weights reshaped matrix is not supported for quantized asymmetric types.
+     * @param[out] output          The output tensor. Should be a 2D Tensor if there are no groups and the weights are not shared; a 3D Tensor otherwise.
+     *                             Data types supported: Same as @p input
+     * @param[in]  num_groups      (Optional) Number of groups when performing a grouped convolution. num_groups != 1 is only supported for NCHW data layout
+     *                             Number of groups greater than one are only supported for NCHW data layout, and the number of weights must be a multiple of it.
+     */
+    void configure(CLCompileContext &compile_context, const ICLTensor *input, const ICLTensor *biases, ICLTensor *output, unsigned int num_groups = 1);
     /** Static function to check if given info will lead to a valid configuration of @ref CLWeightsReshapeKernel
      *
      * @param[in] input      The input tensor to convert. Weights are 4D tensor with dimensions [kernel_x, kernel_y, IFM, OFM] if shared,
diff --git a/arm_compute/core/CL/kernels/CLWidthConcatenate2TensorsKernel.h b/arm_compute/core/CL/kernels/CLWidthConcatenate2TensorsKernel.h
index 1a78144..50abf65 100644
--- a/arm_compute/core/CL/kernels/CLWidthConcatenate2TensorsKernel.h
+++ b/arm_compute/core/CL/kernels/CLWidthConcatenate2TensorsKernel.h
@@ -57,6 +57,14 @@
      * @param[out] output Output tensor. Data types supported: Same as @p input1.
      */
     void configure(const ICLTensor *input1, const ICLTensor *input2, ICLTensor *output);
+    /** Initialise the kernel's input1s and output
+     *
+     * @param[in]  compile_context The compile context to be used.
+     * @param[in]  input1          First input tensor. Data types supported: All.
+     * @param[in]  input2          Second input tensor. Data types supported: same as @p input1
+     * @param[out] output          Output tensor. Data types supported: Same as @p input1.
+     */
+    void configure(CLCompileContext &compile_context, const ICLTensor *input1, const ICLTensor *input2, ICLTensor *output);
     /**  Static function to check if given info will lead to a valid configuration of @ref CLWidthConcatenate2TensorsKernel
      *
      * @param[in] input1 First tensor info. Data types supported: All.
diff --git a/arm_compute/core/CL/kernels/CLWidthConcatenate4TensorsKernel.h b/arm_compute/core/CL/kernels/CLWidthConcatenate4TensorsKernel.h
index 34b8257..f203602 100644
--- a/arm_compute/core/CL/kernels/CLWidthConcatenate4TensorsKernel.h
+++ b/arm_compute/core/CL/kernels/CLWidthConcatenate4TensorsKernel.h
@@ -59,6 +59,16 @@
      * @param[out] output Output tensor. Data types supported: Same as @p input1.
      */
     void configure(const ICLTensor *input1, const ICLTensor *input2, const ICLTensor *input3, const ICLTensor *input4, ICLTensor *output);
+    /** Initialise the kernel's input1s and output
+     *
+     * @param[in]  compile_context The compile context to be used.
+     * @param[in]  input1          First input tensor. Data types supported: All.
+     * @param[in]  input2          Second input tensor. Data types supported: same as @p input1
+     * @param[in]  input3          Third input tensor. Data types supported: same as @p input1
+     * @param[in]  input4          Fourth input tensor. Data types supported: same as @p input1
+     * @param[out] output          Output tensor. Data types supported: Same as @p input1.
+     */
+    void configure(CLCompileContext &compile_context, const ICLTensor *input1, const ICLTensor *input2, const ICLTensor *input3, const ICLTensor *input4, ICLTensor *output);
     /**  Static function to check if given info will lead to a valid configuration of @ref CLWidthConcatenate4TensorsKernel
      *
      * @param[in] input1 First tensor info. Data types supported: All.
diff --git a/arm_compute/core/CL/kernels/CLWidthConcatenateLayerKernel.h b/arm_compute/core/CL/kernels/CLWidthConcatenateLayerKernel.h
index 5dcae67..4564d77 100644
--- a/arm_compute/core/CL/kernels/CLWidthConcatenateLayerKernel.h
+++ b/arm_compute/core/CL/kernels/CLWidthConcatenateLayerKernel.h
@@ -58,6 +58,15 @@
      *
      */
     void configure(const ICLTensor *input, unsigned int width_offset, ICLTensor *output);
+    /** Initialise the kernel's inputs and output
+     *
+     * @param[in]     compile_context The compile context to be used.
+     * @param[in]     input           Input tensor. Data types supported: All.
+     * @param[in]     width_offset    The offset on the X axis.
+     * @param[in,out] output          Output tensor. Data types supported: Same as @p input.
+     *
+     */
+    void configure(CLCompileContext &compile_context, const ICLTensor *input, unsigned int width_offset, ICLTensor *output);
     /**  Static function to check if given info will lead to a valid configuration of @ref CLWidthConcatenateLayerKernel
      *
      * @param[in] input        Input tensor info. Data types supported: All.
diff --git a/arm_compute/core/CL/kernels/CLWinogradFilterTransformKernel.h b/arm_compute/core/CL/kernels/CLWinogradFilterTransformKernel.h
index 4b1de0f..bc7573d 100644
--- a/arm_compute/core/CL/kernels/CLWinogradFilterTransformKernel.h
+++ b/arm_compute/core/CL/kernels/CLWinogradFilterTransformKernel.h
@@ -1,5 +1,5 @@
 /*
- * Copyright (c) 2018-2019 ARM Limited.
+ * Copyright (c) 2018-2020 ARM Limited.
  *
  * SPDX-License-Identifier: MIT
  *
@@ -64,6 +64,25 @@
      * @param[in]  winograd_info Contains Winograd's information described in @ref WinogradInfo
      */
     void configure(const ICLTensor *input, ICLTensor *output, const WinogradInfo &winograd_info);
+    /** Set the input and output tensor.
+     *
+     * @note Winograd filter transform supports the following configurations for NCWH data layout
+     *       F(output tile, kernel size):F(2x2, 3x3), F(2x1, 3x1), F(1x2, 1x3),
+     *                                   F(4x4, 3x3), F(4x1, 3x1), F(1x4, 1x3),
+     *                                   F(4x4, 5x5), F(4x1, 5x1), F(1x4, 1x5)
+     *
+     * @note Winograd filter transform supports the following configurations for NHWC data layout
+     *       F(output tile, kernel size):F(4x4, 3x3), F(4x1, 3x1), F(1x4, 1x3),
+     *                                   F(4x4, 5x5), F(4x1, 5x1), F(1x4, 1x5)
+     *
+     *       Strides: only unit strides
+     *
+     * @param[in]  compile_context The compile context to be used.
+     * @param[in]  input           Source tensor. The input is a 4D tensor with dimensions [kernel_x, kernel_y, IFM, OFM] (NCHW data layout) or [IFM, kernel_x, kernel_y, OFM] (NHWC data layout). Data types supported: F16/F32.
+     * @param[out] output          The output tensor. The shape for this tensor can be calculated using the utility function @p compute_winograd_filter_transform_shape. Data types supported: Same as @p input
+     * @param[in]  winograd_info   Contains Winograd's information described in @ref WinogradInfo
+     */
+    void configure(CLCompileContext &compile_context, const ICLTensor *input, ICLTensor *output, const WinogradInfo &winograd_info);
     /** Static function to check if given info will lead to a valid configuration of @ref CLWinogradFilterTransformKernel
      *
      * @note Winograd filter transform supports the following configurations for NCWH data layout
diff --git a/arm_compute/core/CL/kernels/CLWinogradInputTransformKernel.h b/arm_compute/core/CL/kernels/CLWinogradInputTransformKernel.h
index 03c215b..6bb8d6e 100644
--- a/arm_compute/core/CL/kernels/CLWinogradInputTransformKernel.h
+++ b/arm_compute/core/CL/kernels/CLWinogradInputTransformKernel.h
@@ -1,5 +1,5 @@
 /*
- * Copyright (c) 2018 ARM Limited.
+ * Copyright (c) 2018-2020 ARM Limited.
  *
  * SPDX-License-Identifier: MIT
  *
@@ -62,6 +62,25 @@
      * @param[in] winograd_info Contains Winograd's information described in @ref WinogradInfo.
      */
     void configure(const ICLTensor *input, ICLTensor *output, const WinogradInfo &winograd_info);
+    /** Set the input and output of the kernel.
+     *
+     * @note Winograd input transform supports the following configurations for NCWH data layout
+     *       F(output tile, kernel size):F(2x2, 3x3), F(2x1, 3x1), F(1x2, 1x3),
+     *                                   F(4x4, 3x3), F(4x1, 3x1), F(1x4, 1x3),
+     *                                   F(4x4, 5x5), F(4x1, 5x1), F(1x4, 1x5)
+     *
+     * @note Winograd input transform supports the following configurations for NHWC data layout
+     *       F(output tile, kernel size):F(4x4, 3x3), F(4x1, 3x1), F(1x4, 1x3),
+     *                                   F(4x4, 5x5), F(4x1, 5x1), F(1x4, 1x5)
+     *
+     *       Strides: only unit strides
+     *
+     * @param[in] compile_context The compile context to be used.
+     * @param[in] input           The input tensor to transform. Data types supported: F16/F32
+     * @param[in] output          The output tensor. The shape for this tensor can be calculated using the utility function @p compute_winograd_input_transform_shape. Data types supported: Same as @p input
+     * @param[in] winograd_info   Contains Winograd's information described in @ref WinogradInfo.
+     */
+    void configure(CLCompileContext &compile_context, const ICLTensor *input, ICLTensor *output, const WinogradInfo &winograd_info);
     /** Static function to check if given info will lead to a valid configuration of @ref CLWinogradInputTransformKernel
      *
      * @note Winograd input transform supports the following configurations for NCWH data layout
diff --git a/arm_compute/core/CL/kernels/CLWinogradOutputTransformKernel.h b/arm_compute/core/CL/kernels/CLWinogradOutputTransformKernel.h
index c61e786..aab244b 100644
--- a/arm_compute/core/CL/kernels/CLWinogradOutputTransformKernel.h
+++ b/arm_compute/core/CL/kernels/CLWinogradOutputTransformKernel.h
@@ -1,5 +1,5 @@
 /*
- * Copyright (c) 2018-2019 ARM Limited.
+ * Copyright (c) 2018-2020 ARM Limited.
  *
  * SPDX-License-Identifier: MIT
  *
@@ -66,6 +66,28 @@
      * @param[in]  act_info      (Optional) Activation layer information in case of a fused activation.
      */
     void configure(const ICLTensor *input, const ICLTensor *bias, ICLTensor *output, const WinogradInfo &winograd_info, const ActivationLayerInfo &act_info = ActivationLayerInfo());
+    /** Set the input and output tensor.
+     *
+     * @note Winograd output transform supports the following configurations for NCWH data layout
+     *       F(output tile, kernel size):F(2x2, 3x3), F(2x1, 3x1), F(1x2, 1x3),
+     *                                   F(4x4, 3x3), F(4x1, 3x1), F(1x4, 1x3),
+     *                                   F(4x4, 5x5), F(4x1, 5x1), F(1x4, 1x5)
+     *
+     * @note Winograd output transform supports the following configurations for NHWC data layout
+     *       F(output tile, kernel size):F(4x4, 3x3), F(4x1, 3x1), F(1x4, 1x3),
+     *                                   F(4x4, 5x5), F(4x1, 5x1), F(1x4, 1x5)
+     *
+     *       Strides: only unit strides
+     *
+     * @param[in]  compile_context The compile context to be used.
+     * @param[in]  input           Source tensor with shape [C, N, K, batches]. Data types supported: F16/F32.
+     * @param[in]  bias            Biases tensor. Shared biases supported. Biases are 1D tensor with dimensions [OFM]. It can be a nullptr. Data type supported: as @p input
+     * @param[out] output          The output tensor. The shape for this tensor can be calculated using the utility function @p compute_winograd_output_transform_shape. Data types supported: Same as @p input
+     * @param[in]  winograd_info   Contains Winograd's information described in @ref WinogradInfo
+     * @param[in]  act_info        (Optional) Activation layer information in case of a fused activation.
+     */
+    void configure(CLCompileContext &compile_context, const ICLTensor *input, const ICLTensor *bias, ICLTensor *output, const WinogradInfo &winograd_info,
+                   const ActivationLayerInfo &act_info = ActivationLayerInfo());
 
     /** Static function to check if given info will lead to a valid configuration of @ref CLWinogradOutputTransformKernel
      *
diff --git a/arm_compute/core/CL/kernels/CLYOLOLayerKernel.h b/arm_compute/core/CL/kernels/CLYOLOLayerKernel.h
index 1fae0ed..c03fc94 100644
--- a/arm_compute/core/CL/kernels/CLYOLOLayerKernel.h
+++ b/arm_compute/core/CL/kernels/CLYOLOLayerKernel.h
@@ -1,5 +1,5 @@
 /*
- * Copyright (c) 2018-2019 ARM Limited.
+ * Copyright (c) 2018-2020 ARM Limited.
  *
  * SPDX-License-Identifier: MIT
  *
@@ -62,6 +62,18 @@
      * @param[in]      num_classes Number of classes to activate (must be submultiple of @p input channels)
      */
     void configure(ICLTensor *input, ICLTensor *output, const ActivationLayerInfo &act_info, int32_t num_classes);
+    /** Set the input and output tensor.
+     *
+     * @note If the output tensor is a nullptr, the activation function will be performed in-place
+     *
+     * @param[in]      compile_context The compile context to be used.
+     * @param[in, out] input           Source tensor. In case of @p output tensor = nullptr, this tensor will store the result
+     *                                 of the activation function. Data types supported: F16/F32.
+     * @param[out]     output          Destination tensor. Data type supported: same as @p input
+     * @param[in]      act_info        Activation layer information.
+     * @param[in]      num_classes     Number of classes to activate (must be submultiple of @p input channels)
+     */
+    void configure(CLCompileContext &compile_context, ICLTensor *input, ICLTensor *output, const ActivationLayerInfo &act_info, int32_t num_classes);
     /** Static function to check if given info will lead to a valid configuration of @ref CLYOLOLayerKernel
      *
      * @param[in] input       Source tensor info. In case of @p output tensor info = nullptr, this tensor will store the result
diff --git a/arm_compute/core/CL/kernels/ICLDepthwiseConvolutionLayer3x3Kernel.h b/arm_compute/core/CL/kernels/ICLDepthwiseConvolutionLayer3x3Kernel.h
index 9c62f96..040ca15 100644
--- a/arm_compute/core/CL/kernels/ICLDepthwiseConvolutionLayer3x3Kernel.h
+++ b/arm_compute/core/CL/kernels/ICLDepthwiseConvolutionLayer3x3Kernel.h
@@ -1,5 +1,5 @@
 /*
- * Copyright (c) 2017-2019 ARM Limited.
+ * Copyright (c) 2017-2020 ARM Limited.
  *
  * SPDX-License-Identifier: MIT
  *
@@ -68,6 +68,27 @@
     virtual void configure(const ICLTensor *input, const ICLTensor *weights, const ICLTensor *biases, ICLTensor *output, const PadStrideInfo &conv_info,
                            unsigned int depth_multiplier = 1, ActivationLayerInfo act_info = ActivationLayerInfo(), const Size2D &dilation = Size2D(1U, 1U),
                            const ICLTensor *output_multipliers = nullptr, const ICLTensor *output_shifts = nullptr) = 0;
+    /** Initialize the function's source, destination, conv and border_size.
+     *
+     * @param[in]  compile_context    The compile context to be used.
+     * @param[in]  input              Source tensor. DataType supported: QASYMM8/F16/F32.
+     * @param[in]  weights            Weights tensor. A 3D tensor with dimensions [3, 3, IFM].
+     *                                Data type supported: Same as @p input, QASYMM8/QSYMM8_PER_CHANNEL when input is QASYMM8.
+     * @param[in]  biases             Biases tensor. A 1D tensor with dimensions [IFM]. Must be nullptr if not needed.
+     *                                Data type supported: Same as @p input, S32 when input is QASYMM8.
+     * @param[out] output             Destination tensor. Data type supported: Same as @p input.
+     * @param[in]  conv_info          Padding and stride information to use for the convolution.
+     * @param[in]  depth_multiplier   (Optional) Multiplier to apply to the input's depth in order to retrieve the output's depth. Defaults to 1.
+     * @param[in]  act_info           (Optional) Activation layer information in case of a fused activation. Only RELU, BOUNDED_RELU and LU_BOUNDED_RELU are supported for QASYMM8.
+     * @param[in]  dilation           (Optional) Dilation, in elements, across x and y. Defaults to (1, 1).
+     * @param[in]  output_multipliers (Optional) Output multipliers tensor for quantized computations. In case of per-channel quantization,
+     *                                the number of multipliers must be equal to the number of filters (IFM). Supported data types: S32
+     * @param[in]  output_shifts      (Optional) Output shifts tensor for quantized computations. In case of per-channel quantization,
+     *                                the number of multipliers must be equal to the number of filters (IFM). Supported data types: S32
+     */
+    virtual void configure(CLCompileContext &compile_context, const ICLTensor *input, const ICLTensor *weights, const ICLTensor *biases, ICLTensor *output, const PadStrideInfo &conv_info,
+                           unsigned int depth_multiplier = 1, ActivationLayerInfo act_info = ActivationLayerInfo(), const Size2D &dilation = Size2D(1U, 1U),
+                           const ICLTensor *output_multipliers = nullptr, const ICLTensor *output_shifts = nullptr) = 0;
 
 protected:
     BorderSize       _border_size;
diff --git a/src/core/CL/kernels/CLAbsoluteDifferenceKernel.cpp b/src/core/CL/kernels/CLAbsoluteDifferenceKernel.cpp
index 557046e..52ca1d1 100644
--- a/src/core/CL/kernels/CLAbsoluteDifferenceKernel.cpp
+++ b/src/core/CL/kernels/CLAbsoluteDifferenceKernel.cpp
@@ -1,5 +1,5 @@
 /*
- * Copyright (c) 2016-2019 ARM Limited.
+ * Copyright (c) 2016-2020 ARM Limited.
  *
  * SPDX-License-Identifier: MIT
  *
@@ -46,6 +46,11 @@
 
 void CLAbsoluteDifferenceKernel::configure(const ICLTensor *input1, const ICLTensor *input2, ICLTensor *output)
 {
+    configure(CLKernelLibrary::get().get_compile_context(), input1, input2, output);
+}
+
+void CLAbsoluteDifferenceKernel::configure(CLCompileContext &compile_context, const ICLTensor *input1, const ICLTensor *input2, ICLTensor *output)
+{
     ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input1, 1, DataType::U8, DataType::S16);
     ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input2, 1, DataType::U8, DataType::S16);
     ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(output, 1, DataType::U8, DataType::S16);
@@ -63,7 +68,7 @@
     build_opts.insert("-DDATA_TYPE_OUT=" + get_cl_type_from_data_type(output->info()->data_type()));
 
     // Create kernel
-    _kernel = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel("absdiff", build_opts));
+    _kernel = create_kernel(compile_context, "absdiff", build_opts);
 
     // Configure kernel window
     constexpr unsigned int num_elems_processed_per_iteration = 16;
diff --git a/src/core/CL/kernels/CLAccumulateKernel.cpp b/src/core/CL/kernels/CLAccumulateKernel.cpp
index 12ee210..aa13b4a 100644
--- a/src/core/CL/kernels/CLAccumulateKernel.cpp
+++ b/src/core/CL/kernels/CLAccumulateKernel.cpp
@@ -1,5 +1,5 @@
 /*
- * Copyright (c) 2016-2019 ARM Limited.
+ * Copyright (c) 2016-2020 ARM Limited.
  *
  * SPDX-License-Identifier: MIT
  *
@@ -40,11 +40,16 @@
 
 void CLAccumulateKernel::configure(const ICLTensor *input, ICLTensor *accum)
 {
+    configure(CLKernelLibrary::get().get_compile_context(), input, accum);
+}
+
+void CLAccumulateKernel::configure(CLCompileContext &compile_context, const ICLTensor *input, ICLTensor *accum)
+{
     ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::U8);
     ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(accum, 1, DataType::S16);
 
     // Create kernel
-    _kernel = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel("accumulate"));
+    _kernel = create_kernel(compile_context, "accumulate");
 
     // Make sure _kernel is initialized before calling the parent's configure
     ICLSimple2DKernel::configure(input, accum, num_elems_processed_per_iteration);
@@ -52,12 +57,17 @@
 
 void CLAccumulateWeightedKernel::configure(const ICLTensor *input, float alpha, ICLTensor *accum)
 {
+    configure(CLKernelLibrary::get().get_compile_context(), input, alpha, accum);
+}
+
+void CLAccumulateWeightedKernel::configure(CLCompileContext &compile_context, const ICLTensor *input, float alpha, ICLTensor *accum)
+{
     ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::U8);
     ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(accum, 1, DataType::U8);
     ARM_COMPUTE_ERROR_ON(alpha < 0.0 || alpha > 1.0);
 
     // Create kernel
-    _kernel = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel("accumulate_weighted"));
+    _kernel = create_kernel(compile_context, "accumulate_weighted");
 
     // Set static kernel arguments
     unsigned int idx = 2 * num_arguments_per_2D_tensor(); //Skip the input and output parameters
@@ -69,12 +79,17 @@
 
 void CLAccumulateSquaredKernel::configure(const ICLTensor *input, uint32_t shift, ICLTensor *accum)
 {
+    configure(CLKernelLibrary::get().get_compile_context(), input, shift, accum);
+}
+
+void CLAccumulateSquaredKernel::configure(CLCompileContext &compile_context, const ICLTensor *input, uint32_t shift, ICLTensor *accum)
+{
     ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::U8);
     ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(accum, 1, DataType::S16);
     ARM_COMPUTE_ERROR_ON(shift > 15);
 
     // Create kernel
-    _kernel = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel("accumulate_squared"));
+    _kernel = create_kernel(compile_context, "accumulate_squared");
 
     // Set static kernel arguments
     unsigned int idx = 2 * num_arguments_per_2D_tensor(); //Skip the input and output parameters
diff --git a/src/core/CL/kernels/CLActivationLayerKernel.cpp b/src/core/CL/kernels/CLActivationLayerKernel.cpp
index 2ab0240..15ae8e3 100644
--- a/src/core/CL/kernels/CLActivationLayerKernel.cpp
+++ b/src/core/CL/kernels/CLActivationLayerKernel.cpp
@@ -115,13 +115,18 @@
 }
 } // namespace
 
-CLActivationLayerKernel::CLActivationLayerKernel(CLCoreRuntimeContext *ctx)
-    : _input(nullptr), _output(nullptr), _run_in_place(false), _ctx(ctx)
+CLActivationLayerKernel::CLActivationLayerKernel()
+    : _input(nullptr), _output(nullptr), _run_in_place(false)
 {
 }
 
 void CLActivationLayerKernel::configure(ICLTensor *input, ICLTensor *output, ActivationLayerInfo act_info)
 {
+    configure(CLKernelLibrary::get().get_compile_context(), input, output, act_info);
+}
+
+void CLActivationLayerKernel::configure(CLCompileContext &compile_context, ICLTensor *input, ICLTensor *output, ActivationLayerInfo act_info)
+{
     ARM_COMPUTE_ERROR_ON_NULLPTR(input);
 
     _run_in_place = (output == nullptr) || (output == input);
@@ -226,7 +231,8 @@
     }
 
     // Create kernel
-    _kernel = create_opencl_kernel(_ctx, kernel_name, build_opts);
+    _kernel = create_kernel(compile_context, kernel_name, build_opts.options());
+
     // Make sure _kernel is initialized before calling the parent's configure
     _input  = input;
     _output = output;
diff --git a/src/core/CL/kernels/CLArgMinMaxLayerKernel.cpp b/src/core/CL/kernels/CLArgMinMaxLayerKernel.cpp
index 21709a4..4e33744 100644
--- a/src/core/CL/kernels/CLArgMinMaxLayerKernel.cpp
+++ b/src/core/CL/kernels/CLArgMinMaxLayerKernel.cpp
@@ -116,6 +116,11 @@
 
 void CLArgMinMaxLayerKernel::configure(const ICLTensor *input, const ICLTensor *prev_output, ICLTensor *output, unsigned int axis, ReductionOperation op)
 {
+    configure(CLKernelLibrary::get().get_compile_context(), input, prev_output, output, axis, op);
+}
+
+void CLArgMinMaxLayerKernel::configure(CLCompileContext &compile_context, const ICLTensor *input, const ICLTensor *prev_output, ICLTensor *output, unsigned int axis, ReductionOperation op)
+{
     ARM_COMPUTE_ERROR_ON_NULLPTR(input, output);
     ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(input->info(), (prev_output != nullptr) ? prev_output->info() : nullptr, output->info(), axis, op));
     auto win_config = validate_and_configure_window(input->info(), (prev_output != nullptr) ? prev_output->info() : nullptr, output->info(), axis, op);
@@ -167,7 +172,7 @@
         default:
             ARM_COMPUTE_ERROR("Not supported");
     }
-    _kernel = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel("arg_min_max_" + kernel_axis_name, build_opts.options()));
+    _kernel = create_kernel(compile_context, "arg_min_max_" + kernel_axis_name, build_opts.options());
 
     // Configure kernel window
     ICLKernel::configure_internal(std::get<1>(win_config), lws_hint);
diff --git a/src/core/CL/kernels/CLBatchConcatenateLayerKernel.cpp b/src/core/CL/kernels/CLBatchConcatenateLayerKernel.cpp
index e6e2cb9..610d8e8 100644
--- a/src/core/CL/kernels/CLBatchConcatenateLayerKernel.cpp
+++ b/src/core/CL/kernels/CLBatchConcatenateLayerKernel.cpp
@@ -86,6 +86,11 @@
 
 void CLBatchConcatenateLayerKernel::configure(const ICLTensor *input, unsigned int batch_offset, ICLTensor *output)
 {
+    configure(CLKernelLibrary::get().get_compile_context(), input, batch_offset, output);
+}
+
+void CLBatchConcatenateLayerKernel::configure(CLCompileContext &compile_context, const ICLTensor *input, unsigned int batch_offset, ICLTensor *output)
+{
     ARM_COMPUTE_ERROR_ON_NULLPTR(input, output);
     ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(input->info(), batch_offset, output->info()));
 
@@ -111,7 +116,7 @@
     }
 
     // Create kernel
-    _kernel = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel("concatenate", build_opts.options()));
+    _kernel = create_kernel(compile_context, "concatenate", build_opts.options());
 
     // Configure kernel window
     auto win_config = validate_and_configure_window(input->info(), batch_offset, output->info());
diff --git a/src/core/CL/kernels/CLBatchNormalizationLayerKernel.cpp b/src/core/CL/kernels/CLBatchNormalizationLayerKernel.cpp
index a5c8b1c..8776541 100644
--- a/src/core/CL/kernels/CLBatchNormalizationLayerKernel.cpp
+++ b/src/core/CL/kernels/CLBatchNormalizationLayerKernel.cpp
@@ -139,6 +139,13 @@
 void CLBatchNormalizationLayerKernel::configure(ICLTensor *input, ICLTensor *output, const ICLTensor *mean, const ICLTensor *var, const ICLTensor *beta, const ICLTensor *gamma,
                                                 float epsilon, ActivationLayerInfo act_info)
 {
+    configure(CLKernelLibrary::get().get_compile_context(), input, output, mean, var, beta, gamma, epsilon, act_info);
+}
+
+void CLBatchNormalizationLayerKernel::configure(CLCompileContext &compile_context, ICLTensor *input, ICLTensor *output, const ICLTensor *mean, const ICLTensor *var, const ICLTensor *beta,
+                                                const ICLTensor *gamma,
+                                                float epsilon, ActivationLayerInfo act_info)
+{
     ARM_COMPUTE_ERROR_ON_NULLPTR(input, mean, var);
 
     _input   = input;
@@ -169,7 +176,7 @@
     build_opts.add_option_if(gamma == nullptr, "-DUSE_DEFAULT_GAMMA");
 
     // Create kernel
-    _kernel = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel("batchnormalization_layer_" + lower_string(string_from_data_layout(input->info()->data_layout())), build_opts.options()));
+    _kernel = create_kernel(compile_context, "batchnormalization_layer_" + lower_string(string_from_data_layout(input->info()->data_layout())), build_opts.options());
 
     // Set kernel static arguments
     unsigned int include_output = (!_run_in_place) ? 1 : 0;
diff --git a/src/core/CL/kernels/CLBatchToSpaceLayerKernel.cpp b/src/core/CL/kernels/CLBatchToSpaceLayerKernel.cpp
index 8046213..fbdd04c 100644
--- a/src/core/CL/kernels/CLBatchToSpaceLayerKernel.cpp
+++ b/src/core/CL/kernels/CLBatchToSpaceLayerKernel.cpp
@@ -85,6 +85,11 @@
 
 void CLBatchToSpaceLayerKernel::configure(const ICLTensor *input, const ICLTensor *block_shape, ICLTensor *output)
 {
+    configure(CLKernelLibrary::get().get_compile_context(), input, block_shape, output);
+}
+
+void CLBatchToSpaceLayerKernel::configure(CLCompileContext &compile_context, const ICLTensor *input, const ICLTensor *block_shape, ICLTensor *output)
+{
     ARM_COMPUTE_ERROR_ON_NULLPTR(input, output);
     ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(input->info(), block_shape->info(), output->info()));
 
@@ -99,7 +104,7 @@
     build_opts.add_option("-DDATA_TYPE=" + get_cl_type_from_data_type(input->info()->data_type()));
     build_opts.add_option("-DBATCH_SIZE=" + support::cpp11::to_string(input->info()->dimension(3)));
     build_opts.add_option("-DWIDTH_IN=" + support::cpp11::to_string(input->info()->dimension(idx_width)));
-    _kernel = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel("batch_to_space_" + lower_string(string_from_data_layout(input->info()->data_layout())), build_opts.options()));
+    _kernel = create_kernel(compile_context, "batch_to_space_" + lower_string(string_from_data_layout(input->info()->data_layout())), build_opts.options());
 
     // Configure kernel window
     Window win = calculate_max_window(*input->info(), Steps());
@@ -108,6 +113,11 @@
 
 void CLBatchToSpaceLayerKernel::configure(const ICLTensor *input, const int32_t block_shape_x, const int32_t block_shape_y, ICLTensor *output)
 {
+    configure(CLKernelLibrary::get().get_compile_context(), input, block_shape_x, block_shape_y, output);
+}
+
+void CLBatchToSpaceLayerKernel::configure(CLCompileContext &compile_context, const ICLTensor *input, const int32_t block_shape_x, const int32_t block_shape_y, ICLTensor *output)
+{
     ARM_COMPUTE_ERROR_ON_NULLPTR(input, output);
 
     TensorShape output_shape = compute_batch_to_space_shape(input->info(), block_shape_x, block_shape_y);
@@ -127,7 +137,7 @@
     build_opts.add_option("-DBLOCK_SHAPE_X=" + support::cpp11::to_string(block_shape_x));
     build_opts.add_option("-DBLOCK_SHAPE_Y=" + support::cpp11::to_string(block_shape_y));
     build_opts.add_option("-DWIDTH_IN=" + support::cpp11::to_string(input->info()->dimension(idx_width)));
-    _kernel = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel("batch_to_space_static_" + lower_string(string_from_data_layout(input->info()->data_layout())), build_opts.options()));
+    _kernel = create_kernel(compile_context, "batch_to_space_static_" + lower_string(string_from_data_layout(input->info()->data_layout())), build_opts.options());
 
     // Configure kernel window
     Window win = calculate_max_window(*input->info(), Steps());
diff --git a/src/core/CL/kernels/CLBitwiseAndKernel.cpp b/src/core/CL/kernels/CLBitwiseAndKernel.cpp
index 2d05f2e..df23b90 100644
--- a/src/core/CL/kernels/CLBitwiseAndKernel.cpp
+++ b/src/core/CL/kernels/CLBitwiseAndKernel.cpp
@@ -1,5 +1,5 @@
 /*
- * Copyright (c) 2016-2019 ARM Limited.
+ * Copyright (c) 2016-2020 ARM Limited.
  *
  * SPDX-License-Identifier: MIT
  *
@@ -39,6 +39,11 @@
 }
 void CLBitwiseAndKernel::configure(const ICLTensor *input1, const ICLTensor *input2, ICLTensor *output)
 {
+    configure(CLKernelLibrary::get().get_compile_context(), input1, input2, output);
+}
+
+void CLBitwiseAndKernel::configure(CLCompileContext &compile_context, const ICLTensor *input1, const ICLTensor *input2, ICLTensor *output)
+{
     ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input1, 1, DataType::U8);
     ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input2, 1, DataType::U8);
     ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(output, 1, DataType::U8);
@@ -48,7 +53,7 @@
     _output = output;
 
     // Create kernel
-    _kernel = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel("bitwise_and"));
+    _kernel = create_kernel(compile_context, "bitwise_and");
 
     // Configure kernel window
     constexpr unsigned int num_elems_processed_per_iteration = 16;
diff --git a/src/core/CL/kernels/CLBitwiseNotKernel.cpp b/src/core/CL/kernels/CLBitwiseNotKernel.cpp
index 0098e15..2abfa46 100644
--- a/src/core/CL/kernels/CLBitwiseNotKernel.cpp
+++ b/src/core/CL/kernels/CLBitwiseNotKernel.cpp
@@ -1,5 +1,5 @@
 /*
- * Copyright (c) 2016, 2017 ARM Limited.
+ * Copyright (c) 2016-2020 ARM Limited.
  *
  * SPDX-License-Identifier: MIT
  *
@@ -33,6 +33,11 @@
 
 void CLBitwiseNotKernel::configure(const ICLTensor *input, ICLTensor *output)
 {
+    configure(CLKernelLibrary::get().get_compile_context(), input, output);
+}
+
+void CLBitwiseNotKernel::configure(CLCompileContext &compile_context, const ICLTensor *input, ICLTensor *output)
+{
     ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::U8);
     ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(output, 1, DataType::U8);
 
@@ -40,7 +45,7 @@
     _output = output;
 
     // Create kernel
-    _kernel = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel("bitwise_not"));
+    _kernel = create_kernel(compile_context, "bitwise_not");
 
     // Configure kernel window
     constexpr unsigned int num_elems_processed_per_iteration = 16;
diff --git a/src/core/CL/kernels/CLBitwiseOrKernel.cpp b/src/core/CL/kernels/CLBitwiseOrKernel.cpp
index b3efab8..8ab509a 100644
--- a/src/core/CL/kernels/CLBitwiseOrKernel.cpp
+++ b/src/core/CL/kernels/CLBitwiseOrKernel.cpp
@@ -1,5 +1,5 @@
 /*
- * Copyright (c) 2016-2019 ARM Limited.
+ * Copyright (c) 2016-2020 ARM Limited.
  *
  * SPDX-License-Identifier: MIT
  *
@@ -40,6 +40,11 @@
 
 void CLBitwiseOrKernel::configure(const ICLTensor *input1, const ICLTensor *input2, ICLTensor *output)
 {
+    configure(CLKernelLibrary::get().get_compile_context(), input1, input2, output);
+}
+
+void CLBitwiseOrKernel::configure(CLCompileContext &compile_context, const ICLTensor *input1, const ICLTensor *input2, ICLTensor *output)
+{
     ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input1, 1, DataType::U8);
     ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input2, 1, DataType::U8);
     ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(output, 1, DataType::U8);
@@ -49,7 +54,7 @@
     _output = output;
 
     // Create kernel
-    _kernel = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel("bitwise_or"));
+    _kernel = create_kernel(compile_context, "bitwise_or");
 
     // Configure kernel window
     constexpr unsigned int num_elems_processed_per_iteration = 16;
diff --git a/src/core/CL/kernels/CLBitwiseXorKernel.cpp b/src/core/CL/kernels/CLBitwiseXorKernel.cpp
index d8ac486..c3ff7de 100644
--- a/src/core/CL/kernels/CLBitwiseXorKernel.cpp
+++ b/src/core/CL/kernels/CLBitwiseXorKernel.cpp
@@ -1,5 +1,5 @@
 /*
- * Copyright (c) 2016-2019 ARM Limited.
+ * Copyright (c) 2016-2020 ARM Limited.
  *
  * SPDX-License-Identifier: MIT
  *
@@ -40,6 +40,11 @@
 
 void CLBitwiseXorKernel::configure(const ICLTensor *input1, const ICLTensor *input2, ICLTensor *output)
 {
+    configure(CLKernelLibrary::get().get_compile_context(), input1, input2, output);
+}
+
+void CLBitwiseXorKernel::configure(CLCompileContext &compile_context, const ICLTensor *input1, const ICLTensor *input2, ICLTensor *output)
+{
     ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input1, 1, DataType::U8);
     ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input2, 1, DataType::U8);
     ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(output, 1, DataType::U8);
@@ -49,7 +54,7 @@
     _output = output;
 
     // Create kernel
-    _kernel = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel("bitwise_xor"));
+    _kernel = create_kernel(compile_context, "bitwise_xor");
 
     // Configure kernel window
     constexpr unsigned int num_elems_processed_per_iteration = 16;
diff --git a/src/core/CL/kernels/CLBoundingBoxTransformKernel.cpp b/src/core/CL/kernels/CLBoundingBoxTransformKernel.cpp
index bca23c7..5ed5523 100644
--- a/src/core/CL/kernels/CLBoundingBoxTransformKernel.cpp
+++ b/src/core/CL/kernels/CLBoundingBoxTransformKernel.cpp
@@ -90,6 +90,11 @@
 
 void CLBoundingBoxTransformKernel::configure(const ICLTensor *boxes, ICLTensor *pred_boxes, const ICLTensor *deltas, const BoundingBoxTransformInfo &info)
 {
+    configure(CLKernelLibrary::get().get_compile_context(), boxes, pred_boxes, deltas, info);
+}
+
+void CLBoundingBoxTransformKernel::configure(CLCompileContext &compile_context, const ICLTensor *boxes, ICLTensor *pred_boxes, const ICLTensor *deltas, const BoundingBoxTransformInfo &info)
+{
     ARM_COMPUTE_ERROR_ON_NULLPTR(boxes, pred_boxes, deltas);
     auto_init_if_empty(*pred_boxes->info(), deltas->info()->clone()->set_data_type(boxes->info()->data_type()).set_quantization_info(boxes->info()->quantization_info()));
 
@@ -137,7 +142,7 @@
 
     // Create kernel
     const std::string kernel_name = (is_quantized) ? "bounding_box_transform_quantized" : "bounding_box_transform";
-    _kernel                       = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel(kernel_name, build_opts.options()));
+    _kernel                       = create_kernel(compile_context, kernel_name, build_opts.options());
 
     // Since the number of columns is a multiple of 4 by definition, we don't need to pad the tensor
     const unsigned int num_elems_processed_per_iteration = 4;
diff --git a/src/core/CL/kernels/CLBox3x3Kernel.cpp b/src/core/CL/kernels/CLBox3x3Kernel.cpp
index b81697f..e0979a8 100644
--- a/src/core/CL/kernels/CLBox3x3Kernel.cpp
+++ b/src/core/CL/kernels/CLBox3x3Kernel.cpp
@@ -1,5 +1,5 @@
 /*
- * Copyright (c) 2016-2018 ARM Limited.
+ * Copyright (c) 2016-2020 ARM Limited.
  *
  * SPDX-License-Identifier: MIT
  *
@@ -42,6 +42,11 @@
 
 void CLBox3x3Kernel::configure(const ICLTensor *input, ICLTensor *output, bool border_undefined)
 {
+    configure(CLKernelLibrary::get().get_compile_context(), input, output, border_undefined);
+}
+
+void CLBox3x3Kernel::configure(CLCompileContext &compile_context, const ICLTensor *input, ICLTensor *output, bool border_undefined)
+{
     ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::U8);
     ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(output, 1, DataType::U8);
 
@@ -56,7 +61,7 @@
                                        };
 
     // Create kernel
-    _kernel = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel("convolution3x3_static", build_opts));
+    _kernel = create_kernel(compile_context, "convolution3x3_static", build_opts);
 
     // Configure kernel window
     constexpr unsigned int num_elems_processed_per_iteration = 8;
diff --git a/src/core/CL/kernels/CLCannyEdgeKernel.cpp b/src/core/CL/kernels/CLCannyEdgeKernel.cpp
index 08bfe90..c1aa611 100644
--- a/src/core/CL/kernels/CLCannyEdgeKernel.cpp
+++ b/src/core/CL/kernels/CLCannyEdgeKernel.cpp
@@ -40,6 +40,11 @@
 
 void CLGradientKernel::configure(const ICLTensor *gx, const ICLTensor *gy, ICLTensor *magnitude, ICLTensor *phase, int32_t norm_type)
 {
+    configure(CLKernelLibrary::get().get_compile_context(), gx, gy, magnitude, phase, norm_type);
+}
+
+void CLGradientKernel::configure(CLCompileContext &compile_context, const ICLTensor *gx, const ICLTensor *gy, ICLTensor *magnitude, ICLTensor *phase, int32_t norm_type)
+{
     ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(gx, 1, DataType::S16, DataType::S32);
     ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(gy, 1, DataType::S16, DataType::S32);
     ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(magnitude, 1, DataType::U16, DataType::U32);
@@ -61,7 +66,7 @@
 
     // Create kernel
     const std::string kernel_name = (norm_type == 1) ? std::string("combine_gradients_L1") : std::string("combine_gradients_L2");
-    _kernel                       = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel(kernel_name, built_opts));
+    _kernel                       = create_kernel(compile_context, kernel_name, built_opts);
 
     // Configure kernel window
     constexpr unsigned int num_elems_processed_per_iteration = 4;
@@ -120,6 +125,11 @@
 
 void CLEdgeNonMaxSuppressionKernel::configure(const ICLTensor *magnitude, const ICLTensor *phase, ICLTensor *output, int32_t lower_thr, bool border_undefined)
 {
+    configure(CLKernelLibrary::get().get_compile_context(), magnitude, phase, output, lower_thr, border_undefined);
+}
+
+void CLEdgeNonMaxSuppressionKernel::configure(CLCompileContext &compile_context, const ICLTensor *magnitude, const ICLTensor *phase, ICLTensor *output, int32_t lower_thr, bool border_undefined)
+{
     ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(magnitude, 1, DataType::U16, DataType::U32);
     ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(phase, 1, DataType::U8);
     ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(output, 1, DataType::U16, DataType::U32);
@@ -135,7 +145,7 @@
 
     // Create kernel
     const std::string kernel_name = std::string("suppress_non_maximum");
-    _kernel                       = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel(kernel_name, built_opts));
+    _kernel                       = create_kernel(compile_context, kernel_name, built_opts);
 
     // Set minimum threshold argument
     unsigned int idx = 3 * num_arguments_per_2D_tensor(); //Skip the input and output parameters
@@ -195,6 +205,12 @@
 void CLEdgeTraceKernel::configure(const ICLTensor *input, ICLTensor *output, int32_t upper_thr, int32_t lower_thr,
                                   ICLTensor *visited, ICLTensor *recorded, ICLTensor *l1_stack, ICLTensor *l1_stack_counter)
 {
+    configure(CLKernelLibrary::get().get_compile_context(), input, output, upper_thr, lower_thr, visited, recorded, l1_stack, l1_stack_counter);
+}
+
+void CLEdgeTraceKernel::configure(CLCompileContext &compile_context, const ICLTensor *input, ICLTensor *output, int32_t upper_thr, int32_t lower_thr,
+                                  ICLTensor *visited, ICLTensor *recorded, ICLTensor *l1_stack, ICLTensor *l1_stack_counter)
+{
     ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::U16, DataType::U32);
     ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(output, 1, DataType::U8);
     ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(visited, 1, DataType::U32);
@@ -218,7 +234,7 @@
 
     // Create kernel
     const std::string kernel_name = std::string("hysteresis");
-    _kernel                       = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel(kernel_name, built_opts));
+    _kernel                       = create_kernel(compile_context, kernel_name, built_opts);
 
     // Set constant kernel args
     unsigned int width  = _input->info()->dimension(0);
diff --git a/src/core/CL/kernels/CLChannelCombineKernel.cpp b/src/core/CL/kernels/CLChannelCombineKernel.cpp
index d029efe..90face2 100644
--- a/src/core/CL/kernels/CLChannelCombineKernel.cpp
+++ b/src/core/CL/kernels/CLChannelCombineKernel.cpp
@@ -1,5 +1,5 @@
 /*
- * Copyright (c) 2016-2019 ARM Limited.
+ * Copyright (c) 2016-2020 ARM Limited.
  *
  * SPDX-License-Identifier: MIT
  *
@@ -53,6 +53,11 @@
 
 void CLChannelCombineKernel::configure(const ICLTensor *plane0, const ICLTensor *plane1, const ICLTensor *plane2, const ICLTensor *plane3, ICLTensor *output)
 {
+    configure(CLKernelLibrary::get().get_compile_context(), plane0, plane1, plane2, plane3, output);
+}
+
+void CLChannelCombineKernel::configure(CLCompileContext &compile_context, const ICLTensor *plane0, const ICLTensor *plane1, const ICLTensor *plane2, const ICLTensor *plane3, ICLTensor *output)
+{
     ARM_COMPUTE_ERROR_ON_NULLPTR(plane0, plane1, plane2, output);
     ARM_COMPUTE_ERROR_ON_TENSOR_NOT_2D(plane0);
     ARM_COMPUTE_ERROR_ON_TENSOR_NOT_2D(plane1);
@@ -109,7 +114,7 @@
 
     // Create kernel
     std::string kernel_name = "channel_combine_" + string_from_format(output_format);
-    _kernel                 = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel(kernel_name));
+    _kernel                 = create_kernel(compile_context, kernel_name);
 
     // Configure window
     Window win = calculate_max_window(*output->info(), Steps(num_elems_processed_per_iteration));
@@ -136,6 +141,11 @@
 
 void CLChannelCombineKernel::configure(const ICLImage *plane0, const ICLImage *plane1, const ICLImage *plane2, ICLMultiImage *output)
 {
+    configure(CLKernelLibrary::get().get_compile_context(), plane0, plane1, plane2, output);
+}
+
+void CLChannelCombineKernel::configure(CLCompileContext &compile_context, const ICLImage *plane0, const ICLImage *plane1, const ICLImage *plane2, ICLMultiImage *output)
+{
     ARM_COMPUTE_ERROR_ON_NULLPTR(plane0, plane1, plane2, output);
     ARM_COMPUTE_ERROR_ON_TENSOR_NOT_2D(plane0);
     ARM_COMPUTE_ERROR_ON_TENSOR_NOT_2D(plane1);
@@ -211,7 +221,7 @@
     }
 
     // Create kernel
-    _kernel = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel(kernel_name, build_opts));
+    _kernel = create_kernel(compile_context, kernel_name, build_opts);
 
     // Configure window
     Window win = calculate_max_window(*plane0->info(), Steps(num_elems_processed_per_iteration));
diff --git a/src/core/CL/kernels/CLChannelExtractKernel.cpp b/src/core/CL/kernels/CLChannelExtractKernel.cpp
index d2a0f98..8df162c 100644
--- a/src/core/CL/kernels/CLChannelExtractKernel.cpp
+++ b/src/core/CL/kernels/CLChannelExtractKernel.cpp
@@ -1,5 +1,5 @@
 /*
- * Copyright (c) 2016-2019 ARM Limited.
+ * Copyright (c) 2016-2020 ARM Limited.
  *
  * SPDX-License-Identifier: MIT
  *
@@ -49,6 +49,11 @@
 
 void CLChannelExtractKernel::configure(const ICLTensor *input, Channel channel, ICLTensor *output)
 {
+    configure(CLKernelLibrary::get().get_compile_context(), input, channel, output);
+}
+
+void CLChannelExtractKernel::configure(CLCompileContext &compile_context, const ICLTensor *input, Channel channel, ICLTensor *output)
+{
     ARM_COMPUTE_ERROR_ON_NULLPTR(input, output);
     ARM_COMPUTE_ERROR_ON(input == output);
 
@@ -89,7 +94,7 @@
     // Create kernel
     std::string           kernel_name = "channel_extract_" + string_from_format(format);
     std::set<std::string> build_opts  = { ("-DCHANNEL_" + string_from_channel(channel)) };
-    _kernel                           = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel(kernel_name, build_opts));
+    _kernel                           = create_kernel(compile_context, kernel_name, build_opts);
 
     // Configure window
     Window                 win = calculate_max_window(*input->info(), Steps(_num_elems_processed_per_iteration));
@@ -106,6 +111,11 @@
 
 void CLChannelExtractKernel::configure(const ICLMultiImage *input, Channel channel, ICLImage *output)
 {
+    configure(CLKernelLibrary::get().get_compile_context(), input, channel, output);
+}
+
+void CLChannelExtractKernel::configure(CLCompileContext &compile_context, const ICLMultiImage *input, Channel channel, ICLImage *output)
+{
     ARM_COMPUTE_ERROR_ON_NULLPTR(input, output);
     ARM_COMPUTE_ERROR_ON_TENSOR_NOT_2D(output);
 
@@ -151,7 +161,7 @@
         kernel_name = "channel_extract_" + string_from_format(format);
         build_opts.insert(("-DCHANNEL_" + string_from_channel(channel)));
     }
-    _kernel = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel(kernel_name, build_opts));
+    _kernel = create_kernel(compile_context, kernel_name, build_opts);
 
     // Configure window
     Window                 win = calculate_max_window(*input_plane->info(), Steps(_num_elems_processed_per_iteration));
diff --git a/src/core/CL/kernels/CLChannelShuffleLayerKernel.cpp b/src/core/CL/kernels/CLChannelShuffleLayerKernel.cpp
index 27bf6b9..5e6bbb3 100644
--- a/src/core/CL/kernels/CLChannelShuffleLayerKernel.cpp
+++ b/src/core/CL/kernels/CLChannelShuffleLayerKernel.cpp
@@ -92,6 +92,11 @@
 
 void CLChannelShuffleLayerKernel::configure(const ICLTensor *input, ICLTensor *output, unsigned int num_groups)
 {
+    configure(CLKernelLibrary::get().get_compile_context(), input, output, num_groups);
+}
+
+void CLChannelShuffleLayerKernel::configure(CLCompileContext &compile_context, const ICLTensor *input, ICLTensor *output, unsigned int num_groups)
+{
     ARM_COMPUTE_ERROR_ON_NULLPTR(input, output);
 
     _input  = input;
@@ -116,7 +121,7 @@
     // Create kernel
     std::string kernel_name = "channel_shuffle_" + lower_string(string_from_data_layout(data_layout));
 
-    _kernel = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel(kernel_name, build_opts.options()));
+    _kernel = create_kernel(compile_context, kernel_name, build_opts.options());
 
     // Configure kernel window
     auto win_config = validate_and_configure_window(input->info(), output->info());
diff --git a/src/core/CL/kernels/CLCol2ImKernel.cpp b/src/core/CL/kernels/CLCol2ImKernel.cpp
index 643c2aa..d96ec96 100644
--- a/src/core/CL/kernels/CLCol2ImKernel.cpp
+++ b/src/core/CL/kernels/CLCol2ImKernel.cpp
@@ -91,6 +91,11 @@
 
 void CLCol2ImKernel::configure(const ICLTensor *input, ICLTensor *output, const Size2D &convolved_dims, unsigned int num_groups)
 {
+    configure(CLKernelLibrary::get().get_compile_context(), input, output, convolved_dims, num_groups);
+}
+
+void CLCol2ImKernel::configure(CLCompileContext &compile_context, const ICLTensor *input, ICLTensor *output, const Size2D &convolved_dims, unsigned int num_groups)
+{
     ARM_COMPUTE_ERROR_ON_NULLPTR(input, output);
 
     // Perform validation step
@@ -110,7 +115,7 @@
     build_opts.add_option("-DWIDTH_OUTPUT=" + support::cpp11::to_string(_convolved_dims.width));
     build_opts.add_option("-DNUM_GROUPS=" + support::cpp11::to_string(num_groups));
 
-    _kernel = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel("col2im", build_opts.options()));
+    _kernel = create_kernel(compile_context, "col2im", build_opts.options());
 
     // Configure kernel window
     auto win_config = validate_and_configure_window(input->info(), output->info(), _convolved_dims, num_groups);
diff --git a/src/core/CL/kernels/CLColorConvertKernel.cpp b/src/core/CL/kernels/CLColorConvertKernel.cpp
index f2eb848..720d925 100644
--- a/src/core/CL/kernels/CLColorConvertKernel.cpp
+++ b/src/core/CL/kernels/CLColorConvertKernel.cpp
@@ -48,6 +48,11 @@
 
 void CLColorConvertKernel::configure(const ICLTensor *input, ICLTensor *output)
 {
+    configure(CLKernelLibrary::get().get_compile_context(), input, output);
+}
+
+void CLColorConvertKernel::configure(CLCompileContext &compile_context, const ICLTensor *input, ICLTensor *output)
+{
     ARM_COMPUTE_ERROR_ON(input == nullptr);
     ARM_COMPUTE_ERROR_ON(output == nullptr);
 
@@ -114,7 +119,7 @@
     _output = output;
 
     // Create kernel
-    _kernel = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel(kernel_name.str()));
+    _kernel = create_kernel(compile_context, kernel_name.str());
 
     // Configure kernel window
     Window                 win = calculate_max_window(*input->info(), Steps(num_elems_processed_per_iteration));
@@ -139,6 +144,11 @@
 
 void CLColorConvertKernel::configure(const ICLMultiImage *input, ICLImage *output)
 {
+    configure(CLKernelLibrary::get().get_compile_context(), input, output);
+}
+
+void CLColorConvertKernel::configure(CLCompileContext &compile_context, const ICLMultiImage *input, ICLImage *output)
+{
     ARM_COMPUTE_ERROR_ON_TENSOR_NOT_2D(output);
     ARM_COMPUTE_ERROR_ON(output == nullptr);
 
@@ -180,7 +190,7 @@
     _output      = output;
 
     // Create kernel
-    _kernel = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel(kernel_name.str()));
+    _kernel = create_kernel(compile_context, kernel_name.str());
 
     // Configure kernel window
     const bool  has_two_planes = (input->info()->format() == Format::NV12) || (input->info()->format() == Format::NV21);
@@ -224,6 +234,11 @@
 
 void CLColorConvertKernel::configure(const ICLImage *input, ICLMultiImage *output)
 {
+    configure(CLKernelLibrary::get().get_compile_context(), input, output);
+}
+
+void CLColorConvertKernel::configure(CLCompileContext &compile_context, const ICLImage *input, ICLMultiImage *output)
+{
     ARM_COMPUTE_ERROR_ON_TENSOR_NOT_2D(input);
     ARM_COMPUTE_ERROR_ON(output == nullptr);
 
@@ -289,7 +304,7 @@
     _multi_output = output;
 
     // Create kernel
-    _kernel = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel(kernel_name.str()));
+    _kernel = create_kernel(compile_context, kernel_name.str());
 
     // Configure kernel window
     Window win = calculate_max_window(*input->info(), Steps(num_elems_processed_per_iteration));
@@ -331,6 +346,11 @@
 
 void CLColorConvertKernel::configure(const ICLMultiImage *input, ICLMultiImage *output)
 {
+    configure(CLKernelLibrary::get().get_compile_context(), input, output);
+}
+
+void CLColorConvertKernel::configure(CLCompileContext &compile_context, const ICLMultiImage *input, ICLMultiImage *output)
+{
     unsigned int num_elems_processed_per_iteration = 0;
     switch(input->info()->format())
     {
@@ -387,7 +407,7 @@
     float sub_sampling_input  = (has_two_input_planars || (input->info()->format() == Format::IYUV)) ? 0.5f : 1;
     float sub_sampling_output = (has_two_output_planars || (output->info()->format() == Format::IYUV)) ? 0.5f : 1;
 
-    _kernel = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel(kernel_name.str()));
+    _kernel = create_kernel(compile_context, kernel_name.str());
 
     Window win = calculate_max_window(*input->cl_plane(0)->info(), Steps(num_elems_processed_per_iteration));
     win.set_dimension_step(Window::DimY, 2);
diff --git a/src/core/CL/kernels/CLComparisonKernel.cpp b/src/core/CL/kernels/CLComparisonKernel.cpp
index e010743..61aeebe 100644
--- a/src/core/CL/kernels/CLComparisonKernel.cpp
+++ b/src/core/CL/kernels/CLComparisonKernel.cpp
@@ -108,6 +108,11 @@
 
 void CLComparisonKernel::configure(const ICLTensor *input1, const ICLTensor *input2, ICLTensor *output, ComparisonOperation operation)
 {
+    configure(CLKernelLibrary::get().get_compile_context(), input1, input2, output, operation);
+}
+
+void CLComparisonKernel::configure(CLCompileContext &compile_context, const ICLTensor *input1, const ICLTensor *input2, ICLTensor *output, ComparisonOperation operation)
+{
     ARM_COMPUTE_ERROR_ON_NULLPTR(input1, input2, output);
     ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(*input1->info(), *input2->info(), *output->info(), operation));
 
@@ -141,7 +146,7 @@
     }
 
     // Create kernel
-    _kernel = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel(kernel_name, build_opts));
+    _kernel = create_kernel(compile_context, kernel_name, build_opts);
 
     ICLKernel::configure_internal(win_config.second);
 
diff --git a/src/core/CL/kernels/CLConvertFullyConnectedWeightsKernel.cpp b/src/core/CL/kernels/CLConvertFullyConnectedWeightsKernel.cpp
index 016a7bb..f57ff6c 100644
--- a/src/core/CL/kernels/CLConvertFullyConnectedWeightsKernel.cpp
+++ b/src/core/CL/kernels/CLConvertFullyConnectedWeightsKernel.cpp
@@ -41,6 +41,12 @@
 void CLConvertFullyConnectedWeightsKernel::configure(const ICLTensor *input, ICLTensor *output, const TensorShape &original_input_shape,
                                                      DataLayout data_layout)
 {
+    configure(CLKernelLibrary::get().get_compile_context(), input, output, original_input_shape, data_layout);
+}
+
+void CLConvertFullyConnectedWeightsKernel::configure(CLCompileContext &compile_context, const ICLTensor *input, ICLTensor *output, const TensorShape &original_input_shape,
+                                                     DataLayout data_layout)
+{
     ARM_COMPUTE_ERROR_ON_NULLPTR(input, output);
 
     // Output tensor auto initialisation if not yet initialized
@@ -70,7 +76,7 @@
     build_opts.add_option("-DFACTOR_2=" + support::cpp11::to_string(factor_2));
 
     // Create kernel
-    _kernel = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel("convert_fc_weights", build_opts.options()));
+    _kernel = create_kernel(compile_context, "convert_fc_weights", build_opts.options());
 
     // Configure kernel window
     Window win = calculate_max_window(*input->info(), Steps());
diff --git a/src/core/CL/kernels/CLConvolutionKernel.cpp b/src/core/CL/kernels/CLConvolutionKernel.cpp
index 2e1c56c..3cc6d24 100644
--- a/src/core/CL/kernels/CLConvolutionKernel.cpp
+++ b/src/core/CL/kernels/CLConvolutionKernel.cpp
@@ -60,6 +60,12 @@
 template <unsigned int matrix_size>
 void CLConvolutionKernel<matrix_size>::configure(const ICLTensor *input, ICLTensor *output, const int16_t *conv, uint32_t scale, bool border_undefined)
 {
+    configure(CLKernelLibrary::get().get_compile_context(), input, output, conv, scale, border_undefined);
+}
+
+template <unsigned int matrix_size>
+void CLConvolutionKernel<matrix_size>::configure(CLCompileContext &compile_context, const ICLTensor *input, ICLTensor *output, const int16_t *conv, uint32_t scale, bool border_undefined)
+{
     ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::U8);
     ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(output, 1, DataType::U8, DataType::S16);
     ARM_COMPUTE_ERROR_ON(conv == nullptr);
@@ -92,7 +98,7 @@
     out_type << "-DDATA_TYPE_OUT=" << get_cl_type_from_data_type(output->info()->data_type());
     build_opts.add_option(out_type.str());
 
-    _kernel = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel(kernel_name.str(), build_opts.options()));
+    _kernel = create_kernel(compile_context, kernel_name.str(), build_opts.options());
 
     // Configure kernel window
     constexpr unsigned int num_elems_processed_per_iteration = 8;
@@ -130,6 +136,12 @@
 template <unsigned int matrix_size>
 void CLSeparableConvolutionHorKernel<matrix_size>::configure(const ICLTensor *input, ICLTensor *output, const int16_t *conv, bool border_undefined)
 {
+    configure(CLKernelLibrary::get().get_compile_context(), input, output, conv, border_undefined);
+}
+
+template <unsigned int matrix_size>
+void CLSeparableConvolutionHorKernel<matrix_size>::configure(CLCompileContext &compile_context, const ICLTensor *input, ICLTensor *output, const int16_t *conv, bool border_undefined)
+{
     ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::U8);
     ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(output, 1, DataType::U16, DataType::S16, DataType::S32);
 
@@ -156,7 +168,7 @@
 
     // Create kernel
     const std::string kernel_name = "convolution_separable1x" + support::cpp11::to_string(matrix_size) + "_static";
-    _kernel                       = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel(kernel_name, build_opts));
+    _kernel                       = create_kernel(compile_context, kernel_name, build_opts);
 
     // Configure kernel window
     constexpr unsigned int num_elems_processed_per_iteration = 8;
@@ -200,6 +212,13 @@
 void CLSeparableConvolutionVertKernel<matrix_size>::configure(const ICLTensor *input, ICLTensor *output,
                                                               const int16_t *conv, uint32_t scale, bool border_undefined, DataType data_type)
 {
+    configure(CLKernelLibrary::get().get_compile_context(), input, output, conv, scale, border_undefined, data_type);
+}
+
+template <unsigned int matrix_size>
+void CLSeparableConvolutionVertKernel<matrix_size>::configure(CLCompileContext &compile_context, const ICLTensor *input, ICLTensor *output,
+                                                              const int16_t *conv, uint32_t scale, bool border_undefined, DataType data_type)
+{
     ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::U16, DataType::S16, DataType::S32);
     ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(output, 1, DataType::U8, DataType::S16);
     ARM_COMPUTE_ERROR_ON((matrix_size != 5) && (matrix_size != 7) && (matrix_size != 9));
@@ -230,7 +249,7 @@
 
     // Create kernel
     const std::string kernel_name = "convolution_separable" + support::cpp11::to_string(matrix_size) + "x1_static";
-    _kernel                       = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel(kernel_name, build_opts));
+    _kernel                       = create_kernel(compile_context, kernel_name, build_opts);
 
     // Configure kernel window
     constexpr unsigned int num_elems_processed_per_iteration = 8;
@@ -281,6 +300,12 @@
 
 void CLConvolutionRectangleKernel::configure(const ICLTensor *input, ICLTensor *output, const int16_t *conv, uint32_t width, uint32_t height, uint32_t scale, bool border_undefined)
 {
+    configure(CLKernelLibrary::get().get_compile_context(), input, output, conv, width, height, scale, border_undefined);
+}
+
+void CLConvolutionRectangleKernel::configure(CLCompileContext &compile_context, const ICLTensor *input, ICLTensor *output, const int16_t *conv, uint32_t width, uint32_t height, uint32_t scale,
+                                             bool border_undefined)
+{
     ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::U8);
     ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(output, 1, DataType::U8, DataType::S16);
     ARM_COMPUTE_ERROR_ON(nullptr == conv);
@@ -317,7 +342,7 @@
     options.insert("-DMATRIX_WIDTH=" + support::cpp11::to_string(width));
     options.insert("-DMATRIX_HEIGHT=" + support::cpp11::to_string(height));
 
-    _kernel = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel("convolution_rectangle", options));
+    _kernel = create_kernel(compile_context, "convolution_rectangle", options);
 
     // Configure kernel window
     constexpr unsigned int num_elems_processed_per_iteration = 8;
diff --git a/src/core/CL/kernels/CLCopyKernel.cpp b/src/core/CL/kernels/CLCopyKernel.cpp
index 8a7353b..e59223e 100644
--- a/src/core/CL/kernels/CLCopyKernel.cpp
+++ b/src/core/CL/kernels/CLCopyKernel.cpp
@@ -157,6 +157,11 @@
 
 void CLCopyKernel::configure(const ICLTensor *input, ICLTensor *output, const PaddingList &padding, Window *output_window)
 {
+    configure(CLKernelLibrary::get().get_compile_context(), input, output, padding, output_window);
+}
+
+void CLCopyKernel::configure(CLCompileContext &compile_context, const ICLTensor *input, ICLTensor *output, const PaddingList &padding, Window *output_window)
+{
     ARM_COMPUTE_ERROR_ON_NULLPTR(input, output);
     ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(input->info(), output->info(), padding, output_window));
 
@@ -199,7 +204,7 @@
         }
 
         // Build kernel
-        _kernel = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel("copy_tensor", build_opts.options()));
+        _kernel = create_kernel(compile_context, "copy_tensor", build_opts.options());
     }
     else
     {
@@ -217,7 +222,7 @@
         }
 
         // Build kernel
-        _kernel = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel("copy_pad_tensor", build_opts.options()));
+        _kernel = create_kernel(compile_context, "copy_pad_tensor", build_opts.options());
 
         // Configure window
         win_config = validate_and_configure_window_with_padding(input->info(), output->info(), padding);
diff --git a/src/core/CL/kernels/CLCropKernel.cpp b/src/core/CL/kernels/CLCropKernel.cpp
index e51861e..2c17c99 100644
--- a/src/core/CL/kernels/CLCropKernel.cpp
+++ b/src/core/CL/kernels/CLCropKernel.cpp
@@ -49,6 +49,12 @@
 
 void CLCropKernel::configure(const ICLTensor *input, ICLTensor *output, Coordinates2D start, Coordinates2D end, uint32_t batch_index, float extrapolation_value, Window *output_window)
 {
+    configure(CLKernelLibrary::get().get_compile_context(), input, output, start, end, batch_index, extrapolation_value, output_window);
+}
+
+void CLCropKernel::configure(CLCompileContext &compile_context, const ICLTensor *input, ICLTensor *output, Coordinates2D start, Coordinates2D end, uint32_t batch_index, float extrapolation_value,
+                             Window *output_window)
+{
     ARM_COMPUTE_ERROR_ON_NULLPTR(input, output);
     ARM_COMPUTE_ERROR_THROW_ON(validate(input->info(), output->info(), start, end, batch_index, extrapolation_value, output_window));
 
@@ -86,7 +92,7 @@
     build_opts.add_option_if(multi_access_x && remainder_x, "-DLAST_ACCESSED_X=" + support::cpp11::to_string(std::max<int>(output_width_x - vec_size_x, 0)));
     build_opts.add_option_if(start.x > end.x, "-DWIDTH_FLIPPED=");
     build_opts.add_option_if(start.y > end.y, "-DHEIGHT_FLIPPED=");
-    _kernel = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel("crop_tensor", build_opts.options()));
+    _kernel = create_kernel(compile_context, "crop_tensor", build_opts.options());
 }
 
 Status CLCropKernel::validate(const ITensorInfo *input, const ITensorInfo *output, Coordinates2D start, Coordinates2D end, uint32_t batch_index, float extrapolation_value, Window *output_window)
diff --git a/src/core/CL/kernels/CLDeconvolutionLayerUpsampleKernel.cpp b/src/core/CL/kernels/CLDeconvolutionLayerUpsampleKernel.cpp
index ee39203..f92f7da 100644
--- a/src/core/CL/kernels/CLDeconvolutionLayerUpsampleKernel.cpp
+++ b/src/core/CL/kernels/CLDeconvolutionLayerUpsampleKernel.cpp
@@ -70,6 +70,12 @@
 void CLDeconvolutionLayerUpsampleKernel::configure(const ICLTensor *input, ICLTensor *output,
                                                    const PadStrideInfo &info)
 {
+    configure(CLKernelLibrary::get().get_compile_context(), input, output, info);
+}
+
+void CLDeconvolutionLayerUpsampleKernel::configure(CLCompileContext &compile_context, const ICLTensor *input, ICLTensor *output,
+                                                   const PadStrideInfo &info)
+{
     ARM_COMPUTE_ERROR_ON_NULLPTR(input, output);
 
     // Perform validation step
@@ -83,7 +89,7 @@
     // Create kernel
     CLBuildOptions build_opts;
     build_opts.add_option(("-DDATA_TYPE=" + get_cl_unsigned_type_from_element_size(input->info()->element_size())));
-    _kernel = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel("deconvolution_upsample", build_opts.options()));
+    _kernel = create_kernel(compile_context, "deconvolution_upsample", build_opts.options());
 
     constexpr unsigned int num_elems_processed_per_iteration = 1;
 
diff --git a/src/core/CL/kernels/CLDeconvolutionReshapeOutputKernel.cpp b/src/core/CL/kernels/CLDeconvolutionReshapeOutputKernel.cpp
index 2704c74..68607e9 100644
--- a/src/core/CL/kernels/CLDeconvolutionReshapeOutputKernel.cpp
+++ b/src/core/CL/kernels/CLDeconvolutionReshapeOutputKernel.cpp
@@ -116,6 +116,13 @@
 void CLDeconvolutionReshapeOutputKernel::configure(const ICLTensor *input, const ICLTensor *bias, ICLTensor *output, const ITensorInfo *input_info, const ITensorInfo *weights_info,
                                                    const PadStrideInfo &deconv_info)
 {
+    configure(CLKernelLibrary::get().get_compile_context(), input, bias, output, input_info, weights_info, deconv_info);
+}
+
+void CLDeconvolutionReshapeOutputKernel::configure(CLCompileContext &compile_context, const ICLTensor *input, const ICLTensor *bias, ICLTensor *output, const ITensorInfo *input_info,
+                                                   const ITensorInfo   *weights_info,
+                                                   const PadStrideInfo &deconv_info)
+{
     ARM_COMPUTE_ERROR_ON_NULLPTR(input, output, input_info, weights_info);
     ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(input->info(), (bias != nullptr ? bias->info() : nullptr), output->info(), input_info, weights_info, deconv_info));
 
@@ -148,7 +155,7 @@
     build_opts.add_option_if(data_layout == DataLayout::NCHW, "-DNUM_FILTERS=" + support::cpp11::to_string(filter_b));
     build_opts.add_option_if(_add_bias, "-DADD_BIAS");
 
-    _kernel = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel("deconvolution_reshape", build_opts.options()));
+    _kernel = create_kernel(compile_context, "deconvolution_reshape", build_opts.options());
     ICLKernel::configure_internal(win_config.second);
 
     // Set config_id for enabling LWS tuning
diff --git a/src/core/CL/kernels/CLDepthConcatenateLayerKernel.cpp b/src/core/CL/kernels/CLDepthConcatenateLayerKernel.cpp
index 99489036..241adb2 100644
--- a/src/core/CL/kernels/CLDepthConcatenateLayerKernel.cpp
+++ b/src/core/CL/kernels/CLDepthConcatenateLayerKernel.cpp
@@ -84,6 +84,11 @@
 
 void CLDepthConcatenateLayerKernel::configure(const ICLTensor *input, unsigned int depth_offset, ICLTensor *output)
 {
+    configure(CLKernelLibrary::get().get_compile_context(), input, depth_offset, output);
+}
+
+void CLDepthConcatenateLayerKernel::configure(CLCompileContext &compile_context, const ICLTensor *input, unsigned int depth_offset, ICLTensor *output)
+{
     ARM_COMPUTE_ERROR_ON_NULLPTR(input, output);
     ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(input->info(), depth_offset, output->info()));
 
@@ -109,7 +114,7 @@
     }
 
     // Create kernel
-    _kernel = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel("concatenate", build_opts.options()));
+    _kernel = create_kernel(compile_context, "concatenate", build_opts.options());
 
     // Configure kernel window
     auto win_config = validate_and_configure_window(input->info(), depth_offset, output->info());
diff --git a/src/core/CL/kernels/CLDepthConvertLayerKernel.cpp b/src/core/CL/kernels/CLDepthConvertLayerKernel.cpp
index 13687a54..2e29dbf 100644
--- a/src/core/CL/kernels/CLDepthConvertLayerKernel.cpp
+++ b/src/core/CL/kernels/CLDepthConvertLayerKernel.cpp
@@ -74,6 +74,11 @@
 
 void CLDepthConvertLayerKernel::configure(const ICLTensor *input, ICLTensor *output, ConvertPolicy policy, uint32_t shift)
 {
+    configure(CLKernelLibrary::get().get_compile_context(), input, output, policy, shift);
+}
+
+void CLDepthConvertLayerKernel::configure(CLCompileContext &compile_context, const ICLTensor *input, ICLTensor *output, ConvertPolicy policy, uint32_t shift)
+{
     ARM_COMPUTE_ERROR_ON_NULLPTR(input, output);
 
     // Auto initialize output shape if not initialized (We can only auto-configure the shape, datatype must be given)
@@ -100,14 +105,14 @@
 
     // Create kernel
     const std::string kernel_name = (input_size >= output_size) ? "convert_depth_down" : "convert_depth_up";
-    _kernel                       = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel(kernel_name, build_opts.options()));
+    _kernel                       = create_kernel(compile_context, kernel_name, build_opts.options());
 
     // Set shift arg
     unsigned int idx = 2 * num_arguments_per_3D_tensor(); // Skip the input and output parameters
     _kernel.setArg(idx++, shift);
 
     // Configure kernel
-    ICLSimple3DKernel::configure(input, output, num_elems_processed_per_iteration);
+    ICLSimple2DKernel::configure(input, output, num_elems_processed_per_iteration);
 
     // Collapse window
     const Window &full_window      = window();
diff --git a/src/core/CL/kernels/CLDepthToSpaceLayerKernel.cpp b/src/core/CL/kernels/CLDepthToSpaceLayerKernel.cpp
index ad0d398..cd61a91 100644
--- a/src/core/CL/kernels/CLDepthToSpaceLayerKernel.cpp
+++ b/src/core/CL/kernels/CLDepthToSpaceLayerKernel.cpp
@@ -67,6 +67,11 @@
 
 void CLDepthToSpaceLayerKernel::configure(const ICLTensor *input, ICLTensor *output, int32_t block_shape)
 {
+    configure(CLKernelLibrary::get().get_compile_context(), input, output, block_shape);
+}
+
+void CLDepthToSpaceLayerKernel::configure(CLCompileContext &compile_context, const ICLTensor *input, ICLTensor *output, int32_t block_shape)
+{
     ARM_COMPUTE_ERROR_ON_NULLPTR(input, output);
 
     TensorShape output_shape = compute_depth_to_space_shape(input->info(), block_shape);
@@ -87,7 +92,7 @@
     build_opts.add_option("-DCHANNEL_SIZE=" + support::cpp11::to_string(input->info()->dimension(idx_channel)));
     build_opts.add_option("-DBLOCK_SHAPE=" + support::cpp11::to_string(block_shape));
     build_opts.add_option("-DWIDTH_IN=" + support::cpp11::to_string(input->info()->dimension(idx_width)));
-    _kernel = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel("depth_to_space_" + lower_string(string_from_data_layout(input->info()->data_layout())), build_opts.options()));
+    _kernel = create_kernel(compile_context, "depth_to_space_" + lower_string(string_from_data_layout(input->info()->data_layout())), build_opts.options());
 
     // Configure kernel window
     Window win = calculate_max_window(*input->info(), Steps());
diff --git a/src/core/CL/kernels/CLDepthwiseConvolutionLayer3x3NCHWKernel.cpp b/src/core/CL/kernels/CLDepthwiseConvolutionLayer3x3NCHWKernel.cpp
index a987567..e293fa2 100644
--- a/src/core/CL/kernels/CLDepthwiseConvolutionLayer3x3NCHWKernel.cpp
+++ b/src/core/CL/kernels/CLDepthwiseConvolutionLayer3x3NCHWKernel.cpp
@@ -246,6 +246,13 @@
                                                          const PadStrideInfo &conv_info, unsigned int depth_multiplier, ActivationLayerInfo act_info, const Size2D &dilation,
                                                          const ICLTensor *output_multipliers, const ICLTensor *output_shifts)
 {
+    configure(CLKernelLibrary::get().get_compile_context(), input, weights, biases, output, conv_info, depth_multiplier, act_info, dilation, output_multipliers, output_shifts);
+}
+
+void CLDepthwiseConvolutionLayer3x3NCHWKernel::configure(CLCompileContext &compile_context, const ICLTensor *input, const ICLTensor *weights, const ICLTensor *biases, ICLTensor *output,
+                                                         const PadStrideInfo &conv_info, unsigned int depth_multiplier, ActivationLayerInfo act_info, const Size2D &dilation,
+                                                         const ICLTensor *output_multipliers, const ICLTensor *output_shifts)
+{
     ARM_COMPUTE_ERROR_ON_NULLPTR(input, weights, output);
     ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(input->info(), weights->info(), (biases != nullptr) ? biases->info() : nullptr, output->info(),
                                                   conv_info, depth_multiplier, act_info, dilation,
@@ -337,7 +344,7 @@
     build_opts.add_option_if(input->info()->data_type() == DataType::F16, "-DIS_F16");
     build_opts.add_option_if(input->info()->data_type() == DataType::F32, "-DIS_F32");
 
-    _kernel = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel(kernel_name, build_opts.options()));
+    _kernel = create_kernel(compile_context, kernel_name, build_opts.options());
 
     // Set config_id for enabling LWS tuning
     _config_id = kernel_name;
diff --git a/src/core/CL/kernels/CLDepthwiseConvolutionLayer3x3NHWCKernel.cpp b/src/core/CL/kernels/CLDepthwiseConvolutionLayer3x3NHWCKernel.cpp
index 4afca2b..71af63a 100644
--- a/src/core/CL/kernels/CLDepthwiseConvolutionLayer3x3NHWCKernel.cpp
+++ b/src/core/CL/kernels/CLDepthwiseConvolutionLayer3x3NHWCKernel.cpp
@@ -199,6 +199,13 @@
                                                          const PadStrideInfo &conv_info, unsigned int depth_multiplier, ActivationLayerInfo act_info, const Size2D &dilation,
                                                          const ICLTensor *output_multipliers, const ICLTensor *output_shifts)
 {
+    configure(CLKernelLibrary::get().get_compile_context(), input, weights, biases, output, conv_info, depth_multiplier, act_info, dilation, output_multipliers, output_shifts);
+}
+
+void CLDepthwiseConvolutionLayer3x3NHWCKernel::configure(CLCompileContext &compile_context, const ICLTensor *input, const ICLTensor *weights, const ICLTensor *biases, ICLTensor *output,
+                                                         const PadStrideInfo &conv_info, unsigned int depth_multiplier, ActivationLayerInfo act_info, const Size2D &dilation,
+                                                         const ICLTensor *output_multipliers, const ICLTensor *output_shifts)
+{
     ARM_COMPUTE_ERROR_ON_NULLPTR(input, weights, output);
     ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(input->info(), weights->info(), (biases != nullptr) ? biases->info() : nullptr, output->info(),
                                                   conv_info, depth_multiplier, act_info, dilation,
@@ -328,7 +335,7 @@
     build_opts.add_option_if(input->info()->data_type() == DataType::F32, "-DIS_F32");
 
     ICLKernel::configure_internal(win_config.second);
-    _kernel = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel(kernel_name, build_opts.options()));
+    _kernel = create_kernel(compile_context, kernel_name, build_opts.options());
 
     // Set config_id for enabling LWS tuning
     _config_id = kernel_name;
diff --git a/src/core/CL/kernels/CLDepthwiseConvolutionLayerNativeKernel.cpp b/src/core/CL/kernels/CLDepthwiseConvolutionLayerNativeKernel.cpp
index b4025ff..45df9ed 100644
--- a/src/core/CL/kernels/CLDepthwiseConvolutionLayerNativeKernel.cpp
+++ b/src/core/CL/kernels/CLDepthwiseConvolutionLayerNativeKernel.cpp
@@ -196,6 +196,14 @@
                                                         const DWCKernelInfo &dwc_info, const PadStrideInfo &conv_info, unsigned int depth_multiplier, const Size2D &dilation,
                                                         const ICLTensor *output_multipliers, const ICLTensor *output_shifts)
 {
+    configure(CLKernelLibrary::get().get_compile_context(), input, weights, biases, output, dwc_weights_info, dwc_info, conv_info, depth_multiplier, dilation, output_multipliers, output_shifts);
+}
+
+void CLDepthwiseConvolutionLayerNativeKernel::configure(CLCompileContext &compile_context, const ICLTensor *input, const ICLTensor *weights, const ICLTensor *biases, ICLTensor *output,
+                                                        const DWCWeightsKernelInfo &dwc_weights_info,
+                                                        const DWCKernelInfo &dwc_info, const PadStrideInfo &conv_info, unsigned int depth_multiplier, const Size2D &dilation,
+                                                        const ICLTensor *output_multipliers, const ICLTensor *output_shifts)
+{
     ARM_COMPUTE_ERROR_ON_NULLPTR(input, weights, output);
     ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(input->info(), weights->info(), (biases != nullptr) ? biases->info() : nullptr, output->info(),
                                                   dwc_weights_info, dwc_info, conv_info, depth_multiplier, dilation,
@@ -284,7 +292,7 @@
     }
 
     ICLKernel::configure_internal(win_config.second);
-    _kernel = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel(kernel_name, build_opts.options()));
+    _kernel = create_kernel(compile_context, kernel_name, build_opts.options());
 
     // Set config_id for enabling LWS tuning
     _config_id = kernel_name;
diff --git a/src/core/CL/kernels/CLDepthwiseConvolutionLayerReshapeWeightsKernel.cpp b/src/core/CL/kernels/CLDepthwiseConvolutionLayerReshapeWeightsKernel.cpp
index f746f1f..7e38e77 100644
--- a/src/core/CL/kernels/CLDepthwiseConvolutionLayerReshapeWeightsKernel.cpp
+++ b/src/core/CL/kernels/CLDepthwiseConvolutionLayerReshapeWeightsKernel.cpp
@@ -88,6 +88,11 @@
 
 void CLDepthwiseConvolutionLayerReshapeWeightsKernel::configure(const ICLTensor *input, ICLTensor *output, const DepthwiseConvolutionReshapeInfo &info)
 {
+    configure(CLKernelLibrary::get().get_compile_context(), input, output, info);
+}
+
+void CLDepthwiseConvolutionLayerReshapeWeightsKernel::configure(CLCompileContext &compile_context, const ICLTensor *input, ICLTensor *output, const DepthwiseConvolutionReshapeInfo &info)
+{
     ARM_COMPUTE_ERROR_ON_NULLPTR(input, output);
     ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(input->info(), output->info(), info));
     auto win_config = validate_and_configure_window(input->info(), output->info(), info);
@@ -105,7 +110,7 @@
     build_opts.add_option_if(info.transpose, "-DTRANSPOSE");
     build_opts.add_option("-DDATA_TYPE=" + get_cl_unsigned_type_from_element_size(input->info()->element_size()));
 
-    _kernel = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel("depthwise_convolution_reshape_weights", build_opts.options()));
+    _kernel = create_kernel(compile_context, "depthwise_convolution_reshape_weights", build_opts.options());
 }
 
 Status CLDepthwiseConvolutionLayerReshapeWeightsKernel::validate(const ITensorInfo *input, const ITensorInfo *output, const DepthwiseConvolutionReshapeInfo &info)
diff --git a/src/core/CL/kernels/CLDequantizationLayerKernel.cpp b/src/core/CL/kernels/CLDequantizationLayerKernel.cpp
index 5d9a8fa..ae7489f 100644
--- a/src/core/CL/kernels/CLDequantizationLayerKernel.cpp
+++ b/src/core/CL/kernels/CLDequantizationLayerKernel.cpp
@@ -77,6 +77,11 @@
 
 void CLDequantizationLayerKernel::configure(const ICLTensor *input, ICLTensor *output)
 {
+    configure(CLKernelLibrary::get().get_compile_context(), input, output);
+}
+
+void CLDequantizationLayerKernel::configure(CLCompileContext &compile_context, const ICLTensor *input, ICLTensor *output)
+{
     ARM_COMPUTE_ERROR_ON_NULLPTR(input, output);
     ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(input->info(), output->info()));
 
@@ -120,7 +125,7 @@
     build_opts.add_option_if(multi_access_x, "-DLAST_ACCESSED_X=" + support::cpp11::to_string(std::max<int>(output_width_x - vec_size_x, 0)));
 
     // Create kernel name
-    _kernel = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel(kernel_name, build_opts.options()));
+    _kernel = create_kernel(compile_context, kernel_name, build_opts.options());
 }
 
 Status CLDequantizationLayerKernel::validate(const ITensorInfo *input, const ITensorInfo *output)
diff --git a/src/core/CL/kernels/CLDerivativeKernel.cpp b/src/core/CL/kernels/CLDerivativeKernel.cpp
index bfda041..670cde3 100644
--- a/src/core/CL/kernels/CLDerivativeKernel.cpp
+++ b/src/core/CL/kernels/CLDerivativeKernel.cpp
@@ -50,6 +50,11 @@
 
 void CLDerivativeKernel::configure(const ICLTensor *input, ICLTensor *output_x, ICLTensor *output_y, bool border_undefined)
 {
+    configure(CLKernelLibrary::get().get_compile_context(), input, output_x, output_y, border_undefined);
+}
+
+void CLDerivativeKernel::configure(CLCompileContext &compile_context, const ICLTensor *input, ICLTensor *output_x, ICLTensor *output_y, bool border_undefined)
+{
     ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::U8);
     ARM_COMPUTE_ERROR_ON((output_x == nullptr) && (output_y == nullptr));
 
@@ -85,7 +90,7 @@
 
     // Create kernel
     const std::string kernel_name = std::string("derivative");
-    _kernel                       = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel(kernel_name, build_opts));
+    _kernel                       = create_kernel(compile_context, kernel_name, build_opts);
 
     // Configure kernel window
     constexpr unsigned int num_elems_processed_per_iteration = 16;
diff --git a/src/core/CL/kernels/CLDilateKernel.cpp b/src/core/CL/kernels/CLDilateKernel.cpp
index 89853d7..0f6879d 100644
--- a/src/core/CL/kernels/CLDilateKernel.cpp
+++ b/src/core/CL/kernels/CLDilateKernel.cpp
@@ -1,5 +1,5 @@
 /*
- * Copyright (c) 2016-2018 ARM Limited.
+ * Copyright (c) 2016-2020 ARM Limited.
  *
  * SPDX-License-Identifier: MIT
  *
@@ -38,11 +38,16 @@
 
 void CLDilateKernel::configure(const ICLTensor *input, ICLTensor *output, bool border_undefined)
 {
+    configure(CLKernelLibrary::get().get_compile_context(), input, output, border_undefined);
+}
+
+void CLDilateKernel::configure(CLCompileContext &compile_context, const ICLTensor *input, ICLTensor *output, bool border_undefined)
+{
     ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::U8);
     ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(output, 1, DataType::U8);
 
     // Create kernel
-    _kernel = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel("dilate"));
+    _kernel = create_kernel(compile_context, "dilate");
 
     _input  = input;
     _output = output;
diff --git a/src/core/CL/kernels/CLDirectConvolutionLayerKernel.cpp b/src/core/CL/kernels/CLDirectConvolutionLayerKernel.cpp
index d1dfcd9..ff3d106 100644
--- a/src/core/CL/kernels/CLDirectConvolutionLayerKernel.cpp
+++ b/src/core/CL/kernels/CLDirectConvolutionLayerKernel.cpp
@@ -423,6 +423,12 @@
 
 void CLDirectConvolutionLayerKernel::configure(const ICLTensor *input, const ICLTensor *weights, const ICLTensor *biases, ICLTensor *output, const PadStrideInfo &conv_info)
 {
+    configure(CLKernelLibrary::get().get_compile_context(), input, weights, biases, output, conv_info);
+}
+
+void CLDirectConvolutionLayerKernel::configure(CLCompileContext &compile_context, const ICLTensor *input, const ICLTensor *weights, const ICLTensor *biases, ICLTensor *output,
+                                               const PadStrideInfo &conv_info)
+{
     ARM_COMPUTE_ERROR_ON_NULLPTR(input, weights, output);
 
     _data_layout          = input->info()->data_layout();
@@ -491,7 +497,7 @@
         build_options.add_option(std::string("-DWEIGHTS_DEPTH=" + support::cpp11::to_string(_weights->info()->dimension(channel_idx))));
 
         kernel_name << "_f32_bifrost";
-        _kernel = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel(kernel_name.str(), build_options.options()));
+        _kernel = create_kernel(compile_context, kernel_name.str(), build_options.options());
     }
     else
     {
@@ -535,7 +541,7 @@
             build_options.add_option("-DKERNEL_SIZE=" + support::cpp11::to_string(kernel_size));
 
             // Create kernel
-            _kernel = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel("direct_convolution_quantized", build_options.options()));
+            _kernel = create_kernel(compile_context, "direct_convolution_quantized", build_options.options());
 
             // Set static kernel arguments
             unsigned int idx = 3 * num_arguments_per_3D_tensor() + ((_biases != nullptr) ? num_arguments_per_1D_tensor() : 0) + 1;
@@ -546,7 +552,7 @@
         else
         {
             // Create kernel
-            _kernel = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel(kernel_name.str(), build_options.options()));
+            _kernel = create_kernel(compile_context, kernel_name.str(), build_options.options());
         }
     }
 
diff --git a/src/core/CL/kernels/CLElementWiseUnaryLayerKernel.cpp b/src/core/CL/kernels/CLElementWiseUnaryLayerKernel.cpp
index a1aada4..7356c5a 100644
--- a/src/core/CL/kernels/CLElementWiseUnaryLayerKernel.cpp
+++ b/src/core/CL/kernels/CLElementWiseUnaryLayerKernel.cpp
@@ -52,6 +52,11 @@
 
 void CLElementWiseUnaryLayerKernel::configure(const ICLTensor *input, ICLTensor *output, const ElementWiseUnary &op)
 {
+    configure(CLKernelLibrary::get().get_compile_context(), input, output, op);
+}
+
+void CLElementWiseUnaryLayerKernel::configure(CLCompileContext &compile_context, const ICLTensor *input, ICLTensor *output, const ElementWiseUnary &op)
+{
     ARM_COMPUTE_ERROR_ON_NULLPTR(input, output);
     ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(*input->info(), *output->info()));
 
@@ -105,7 +110,7 @@
     }
 
     // Create kernel
-    _kernel = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel(kernel_name, build_opts.options()));
+    _kernel = create_kernel(compile_context, kernel_name, build_opts.options());
 }
 
 Status CLElementWiseUnaryLayerKernel::validate(const ITensorInfo *input, const ITensorInfo *output, const ElementWiseUnary &op)
diff --git a/src/core/CL/kernels/CLElementwiseOperationKernel.cpp b/src/core/CL/kernels/CLElementwiseOperationKernel.cpp
index 0f2e26f..ee4ef40 100644
--- a/src/core/CL/kernels/CLElementwiseOperationKernel.cpp
+++ b/src/core/CL/kernels/CLElementwiseOperationKernel.cpp
@@ -237,6 +237,11 @@
 
 void CLElementwiseOperationKernel::configure_common(const ICLTensor *input1, const ICLTensor *input2, ICLTensor *output)
 {
+    configure_common(CLKernelLibrary::get().get_compile_context(), input1, input2, output);
+}
+
+void CLElementwiseOperationKernel::configure_common(CLCompileContext &compile_context, const ICLTensor *input1, const ICLTensor *input2, ICLTensor *output)
+{
     ARM_COMPUTE_ERROR_ON_NULLPTR(input1, input2, output);
     ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(*input1->info(), *input2->info(), *output->info()));
 
@@ -264,7 +269,7 @@
     }
 
     // Create kernel
-    _kernel = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel(kernel_name, build_opts.options()));
+    _kernel = create_kernel(compile_context, kernel_name, build_opts.options());
 
     ICLKernel::configure_internal(win_config.second);
 
@@ -329,10 +334,17 @@
 void CLSaturatedArithmeticOperationKernel::configure(ArithmeticOperation op, const ICLTensor *input1, const ICLTensor *input2, ICLTensor *output, const ConvertPolicy &policy,
                                                      const ActivationLayerInfo &act_info)
 {
+    configure(CLKernelLibrary::get().get_compile_context(), op, input1, input2, output, policy, act_info);
+}
+
+void CLSaturatedArithmeticOperationKernel::configure(CLCompileContext &compile_context, ArithmeticOperation op, const ICLTensor *input1, const ICLTensor *input2, ICLTensor *output,
+                                                     const ConvertPolicy       &policy,
+                                                     const ActivationLayerInfo &act_info)
+{
     _policy   = policy;
     _op       = op;
     _act_info = act_info;
-    configure_common(input1, input2, output);
+    configure_common(compile_context, input1, input2, output);
 }
 
 Status CLSaturatedArithmeticOperationKernel::validate(ArithmeticOperation op, const ITensorInfo *input1, const ITensorInfo *input2, const ITensorInfo *output, const ConvertPolicy &policy,
@@ -381,9 +393,15 @@
 
 void CLArithmeticOperationKernel::configure(ArithmeticOperation op, const ICLTensor *input1, const ICLTensor *input2, ICLTensor *output, const ActivationLayerInfo &act_info)
 {
+    configure(CLKernelLibrary::get().get_compile_context(), op, input1, input2, output, act_info);
+}
+
+void CLArithmeticOperationKernel::configure(CLCompileContext &compile_context, ArithmeticOperation op, const ICLTensor *input1, const ICLTensor *input2, ICLTensor *output,
+                                            const ActivationLayerInfo &act_info)
+{
     _op       = op;
     _act_info = act_info;
-    configure_common(input1, input2, output);
+    configure_common(compile_context, input1, input2, output);
 }
 
 Status CLArithmeticOperationKernel::validate(ArithmeticOperation op, const ITensorInfo *input1, const ITensorInfo *input2, const ITensorInfo *output, const ActivationLayerInfo &act_info)
diff --git a/src/core/CL/kernels/CLErodeKernel.cpp b/src/core/CL/kernels/CLErodeKernel.cpp
index e56b71a..e959d1c 100644
--- a/src/core/CL/kernels/CLErodeKernel.cpp
+++ b/src/core/CL/kernels/CLErodeKernel.cpp
@@ -1,5 +1,5 @@
 /*
- * Copyright (c) 2016-2018 ARM Limited.
+ * Copyright (c) 2016-2020 ARM Limited.
  *
  * SPDX-License-Identifier: MIT
  *
@@ -38,11 +38,16 @@
 
 void CLErodeKernel::configure(const ICLTensor *input, ICLTensor *output, bool border_undefined)
 {
+    configure(CLKernelLibrary::get().get_compile_context(), input, output, border_undefined);
+}
+
+void CLErodeKernel::configure(CLCompileContext &compile_context, const ICLTensor *input, ICLTensor *output, bool border_undefined)
+{
     ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::U8);
     ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(output, 1, DataType::U8);
 
     // Create kernel
-    _kernel = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel("erode"));
+    _kernel = create_kernel(compile_context, "erode");
 
     _input  = input;
     _output = output;
diff --git a/src/core/CL/kernels/CLFFTDigitReverseKernel.cpp b/src/core/CL/kernels/CLFFTDigitReverseKernel.cpp
index 822f155..5542ad7 100644
--- a/src/core/CL/kernels/CLFFTDigitReverseKernel.cpp
+++ b/src/core/CL/kernels/CLFFTDigitReverseKernel.cpp
@@ -75,6 +75,11 @@
 
 void CLFFTDigitReverseKernel::configure(const ICLTensor *input, ICLTensor *output, const ICLTensor *idx, const FFTDigitReverseKernelInfo &config)
 {
+    configure(CLKernelLibrary::get().get_compile_context(), input, output, idx, config);
+}
+
+void CLFFTDigitReverseKernel::configure(CLCompileContext &compile_context, const ICLTensor *input, ICLTensor *output, const ICLTensor *idx, const FFTDigitReverseKernelInfo &config)
+{
     ARM_COMPUTE_ERROR_ON_NULLPTR(input, output, idx);
     ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(input->info(), output->info(), idx->info(), config));
 
@@ -87,7 +92,7 @@
     build_opts.add_option("-DVEC_SIZE=" + support::cpp11::to_string(input->info()->num_channels()));
     build_opts.add_option_if(config.conjugate, "-DCONJ");
     std::string kernel_name = "fft_digit_reverse_axis_" + support::cpp11::to_string(config.axis);
-    _kernel                 = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel(kernel_name, build_opts.options()));
+    _kernel                 = create_kernel(compile_context, kernel_name, build_opts.options());
 
     // Configure kernel window
     auto win_config = validate_and_configure_window(input->info(), output->info(), idx->info(), config);
diff --git a/src/core/CL/kernels/CLFFTRadixStageKernel.cpp b/src/core/CL/kernels/CLFFTRadixStageKernel.cpp
index 73df5b2..6e7e1ef 100644
--- a/src/core/CL/kernels/CLFFTRadixStageKernel.cpp
+++ b/src/core/CL/kernels/CLFFTRadixStageKernel.cpp
@@ -85,6 +85,11 @@
 
 void CLFFTRadixStageKernel::configure(ICLTensor *input, ICLTensor *output, const FFTRadixStageKernelInfo &config)
 {
+    configure(CLKernelLibrary::get().get_compile_context(), input, output, config);
+}
+
+void CLFFTRadixStageKernel::configure(CLCompileContext &compile_context, ICLTensor *input, ICLTensor *output, const FFTRadixStageKernelInfo &config)
+{
     ARM_COMPUTE_ERROR_ON_NULLPTR(input);
     ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(input->info(), (output != nullptr) ? output->info() : nullptr, config));
 
@@ -101,7 +106,7 @@
     kernel_name += "_radix_" + support::cpp11::to_string(config.radix);
     kernel_name += (config.is_first_stage) ? "_first_stage" : "";
     kernel_name += "_axis_" + support::cpp11::to_string(config.axis);
-    _kernel = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel(kernel_name, build_opts.options()));
+    _kernel = create_kernel(compile_context, kernel_name, build_opts.options());
 
     // Set static arguments if not the first stage
     if(!config.is_first_stage)
diff --git a/src/core/CL/kernels/CLFFTScaleKernel.cpp b/src/core/CL/kernels/CLFFTScaleKernel.cpp
index 312c737..32e652a 100644
--- a/src/core/CL/kernels/CLFFTScaleKernel.cpp
+++ b/src/core/CL/kernels/CLFFTScaleKernel.cpp
@@ -78,6 +78,11 @@
 
 void CLFFTScaleKernel::configure(ICLTensor *input, ICLTensor *output, const FFTScaleKernelInfo &config)
 {
+    configure(CLKernelLibrary::get().get_compile_context(), input, output, config);
+}
+
+void CLFFTScaleKernel::configure(CLCompileContext &compile_context, ICLTensor *input, ICLTensor *output, const FFTScaleKernelInfo &config)
+{
     ARM_COMPUTE_ERROR_ON_NULLPTR(input);
     ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(input->info(), (output != nullptr) ? output->info() : nullptr));
 
@@ -91,7 +96,7 @@
     build_opts.add_option("-DVEC_SIZE=" + support::cpp11::to_string(output != nullptr ? output->info()->num_channels() : input->info()->num_channels()));
     build_opts.add_option_if(config.conjugate, "-DCONJ");
     std::string kernel_name = "fft_scale_conj";
-    _kernel                 = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel(kernel_name, build_opts.options()));
+    _kernel                 = create_kernel(compile_context, kernel_name, build_opts.options());
 
     // Set static arguments
     unsigned int idx = (1 + (_run_in_place ? 0 : 1)) * num_arguments_per_3D_tensor(); // Skip the input and output parameters
diff --git a/src/core/CL/kernels/CLFastCornersKernel.cpp b/src/core/CL/kernels/CLFastCornersKernel.cpp
index 79ab3b7..2bd4d89 100644
--- a/src/core/CL/kernels/CLFastCornersKernel.cpp
+++ b/src/core/CL/kernels/CLFastCornersKernel.cpp
@@ -50,6 +50,11 @@
 
 void CLFastCornersKernel::configure(const ICLImage *input, ICLImage *output, float threshold, bool non_max_suppression, BorderMode border_mode)
 {
+    configure(CLKernelLibrary::get().get_compile_context(), input, output, threshold, non_max_suppression, border_mode);
+}
+
+void CLFastCornersKernel::configure(CLCompileContext &compile_context, const ICLImage *input, ICLImage *output, float threshold, bool non_max_suppression, BorderMode border_mode)
+{
     ARM_COMPUTE_ERROR_ON_TENSOR_NOT_2D(input);
     ARM_COMPUTE_ERROR_ON_TENSOR_NOT_2D(output);
     ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::U8);
@@ -69,7 +74,7 @@
 
     // Create kernel
     const std::string kernel_name = std::string("fast_corners");
-    _kernel                       = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel(kernel_name, build_opts));
+    _kernel                       = create_kernel(compile_context, kernel_name, build_opts);
 
     // Set static kernel arguments
     unsigned int idx = 2 * num_arguments_per_2D_tensor(); // Skip the input and output parameters
@@ -133,6 +138,11 @@
 
 void CLCopyToArrayKernel::configure(const ICLImage *input, bool update_number, ICLKeyPointArray *corners, cl::Buffer *num_buffers)
 {
+    configure(CLKernelLibrary::get().get_compile_context(), input, update_number, corners, num_buffers);
+}
+
+void CLCopyToArrayKernel::configure(CLCompileContext &compile_context, const ICLImage *input, bool update_number, ICLKeyPointArray *corners, cl::Buffer *num_buffers)
+{
     ARM_COMPUTE_ERROR_ON_TENSOR_NOT_2D(input);
     ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::U8);
     ARM_COMPUTE_ERROR_ON(corners == nullptr);
@@ -151,7 +161,7 @@
 
     // Create kernel
     const std::string kernel_name = std::string("copy_to_keypoint");
-    _kernel                       = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel(kernel_name, build_opts));
+    _kernel                       = create_kernel(compile_context, kernel_name, build_opts);
 
     //Get how many pixels skipped in the x dimension in the previous stages
     unsigned int offset = _input->info()->valid_region().anchor.x();
diff --git a/src/core/CL/kernels/CLFillBorderKernel.cpp b/src/core/CL/kernels/CLFillBorderKernel.cpp
index c7a83fc..c69a8c9 100644
--- a/src/core/CL/kernels/CLFillBorderKernel.cpp
+++ b/src/core/CL/kernels/CLFillBorderKernel.cpp
@@ -62,6 +62,11 @@
 
 void CLFillBorderKernel::configure(ICLTensor *tensor, BorderSize border_size, BorderMode border_mode, const PixelValue &constant_border_value)
 {
+    configure(CLKernelLibrary::get().get_compile_context(), tensor, border_size, border_mode, constant_border_value);
+}
+
+void CLFillBorderKernel::configure(CLCompileContext &compile_context, ICLTensor *tensor, BorderSize border_size, BorderMode border_mode, const PixelValue &constant_border_value)
+{
     ARM_COMPUTE_ERROR_ON(tensor == nullptr);
     ARM_COMPUTE_ERROR_ON(tensor->info()->num_channels() != 1);
 
@@ -87,7 +92,7 @@
     build_opts.add_option("-DBORDER_SIZE_RIGHT=" + support::cpp11::to_string(border_size.right));
 
     // Create kernel
-    _kernel = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel(kernel_name, build_opts.options()));
+    _kernel = create_kernel(compile_context, kernel_name, build_opts.options());
     _tensor = tensor;
 
     // Create static kernel arguments
diff --git a/src/core/CL/kernels/CLFlattenLayerKernel.cpp b/src/core/CL/kernels/CLFlattenLayerKernel.cpp
index c078b0d..c2dc933 100644
--- a/src/core/CL/kernels/CLFlattenLayerKernel.cpp
+++ b/src/core/CL/kernels/CLFlattenLayerKernel.cpp
@@ -82,6 +82,11 @@
 
 void CLFlattenLayerKernel::configure(const ICLTensor *input, ICLTensor *output)
 {
+    configure(CLKernelLibrary::get().get_compile_context(), input, output);
+}
+
+void CLFlattenLayerKernel::configure(CLCompileContext &compile_context, const ICLTensor *input, ICLTensor *output)
+{
     ARM_COMPUTE_ERROR_ON_NULLPTR(input, output);
     ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(input->info(), output->info()));
 
@@ -101,7 +106,7 @@
     build_opts.add_option_if(output->info()->num_dimensions() > 2, "-DDST_DIM1=" + support::cpp11::to_string(output->info()->dimension(1)));
 
     // Create kernel
-    _kernel = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel("flatten", build_opts.options()));
+    _kernel = create_kernel(compile_context, "flatten", build_opts.options());
 
     // Set config_id for enabling LWS tuning
     _config_id = "flatten";
diff --git a/src/core/CL/kernels/CLFuseBatchNormalizationKernel.cpp b/src/core/CL/kernels/CLFuseBatchNormalizationKernel.cpp
index 1e1c3e0..6f4ba0e 100644
--- a/src/core/CL/kernels/CLFuseBatchNormalizationKernel.cpp
+++ b/src/core/CL/kernels/CLFuseBatchNormalizationKernel.cpp
@@ -109,6 +109,14 @@
                                                const ICLTensor *input_bias, const ICLTensor *bn_beta, const ICLTensor *bn_gamma,
                                                float epsilon, FuseBatchNormalizationType fbn_type)
 {
+    configure(CLKernelLibrary::get().get_compile_context(), input_weights, bn_mean, bn_var, fused_weights, fused_bias, input_bias, bn_beta, bn_gamma, epsilon, fbn_type);
+}
+
+void CLFuseBatchNormalizationKernel::configure(CLCompileContext &compile_context, const ICLTensor *input_weights, const ICLTensor *bn_mean, const ICLTensor *bn_var,
+                                               ICLTensor *fused_weights, ICLTensor *fused_bias,
+                                               const ICLTensor *input_bias, const ICLTensor *bn_beta, const ICLTensor *bn_gamma,
+                                               float epsilon, FuseBatchNormalizationType fbn_type)
+{
     ARM_COMPUTE_ERROR_ON_NULLPTR(input_weights, bn_mean, bn_var);
 
     _input_weights = input_weights;
@@ -162,7 +170,7 @@
     build_opts.add_option_if(bn_gamma != nullptr, "-DGAMMA");
 
     // Create kernel
-    _kernel = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel("fuse_batchnormalization_layer", build_opts.options()));
+    _kernel = create_kernel(compile_context, "fuse_batchnormalization_layer", build_opts.options());
 }
 
 Status CLFuseBatchNormalizationKernel::validate(const ITensorInfo *input_weights, const ITensorInfo *bn_mean, const ITensorInfo *bn_var,
diff --git a/src/core/CL/kernels/CLGEMMLowpMatrixMultiplyKernel.cpp b/src/core/CL/kernels/CLGEMMLowpMatrixMultiplyKernel.cpp
index d13884f..0d4bbba 100644
--- a/src/core/CL/kernels/CLGEMMLowpMatrixMultiplyKernel.cpp
+++ b/src/core/CL/kernels/CLGEMMLowpMatrixMultiplyKernel.cpp
@@ -172,6 +172,11 @@
 
 void CLGEMMLowpMatrixMultiplyKernel::configure(const ICLTensor *input0, const ICLTensor *input1, ICLTensor *output, const GEMMReshapeInfo &gemm_info)
 {
+    configure(CLKernelLibrary::get().get_compile_context(), input0, input1, output, gemm_info);
+}
+
+void CLGEMMLowpMatrixMultiplyKernel::configure(CLCompileContext &compile_context, const ICLTensor *input0, const ICLTensor *input1, ICLTensor *output, const GEMMReshapeInfo &gemm_info)
+{
     ARM_COMPUTE_ERROR_ON_NULLPTR(input0, input1, output);
 
     ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(input0->info(), input1->info(), output->info(), gemm_info));
@@ -218,7 +223,7 @@
     kernel_name = "gemmlowp_mm_midgard";
 
     // Create kernel
-    _kernel = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel(kernel_name, build_opts.options()));
+    _kernel = create_kernel(compile_context, kernel_name, build_opts.options());
 
     // Set config_id for enabling LWS tuning
     _config_id = kernel_name;
diff --git a/src/core/CL/kernels/CLGEMMLowpMatrixMultiplyNativeKernel.cpp b/src/core/CL/kernels/CLGEMMLowpMatrixMultiplyNativeKernel.cpp
index 82ba824..bcf7156 100644
--- a/src/core/CL/kernels/CLGEMMLowpMatrixMultiplyNativeKernel.cpp
+++ b/src/core/CL/kernels/CLGEMMLowpMatrixMultiplyNativeKernel.cpp
@@ -173,6 +173,13 @@
 void CLGEMMLowpMatrixMultiplyNativeKernel::configure(const ICLTensor *input0, const ICLTensor *input1, ICLTensor *output, const GEMMLHSMatrixInfo &lhs_info, const GEMMRHSMatrixInfo &rhs_info,
                                                      const GEMMReshapeInfo &gemm_info)
 {
+    configure(CLKernelLibrary::get().get_compile_context(), input0, input1, output, lhs_info, rhs_info, gemm_info);
+}
+
+void CLGEMMLowpMatrixMultiplyNativeKernel::configure(CLCompileContext &compile_context, const ICLTensor *input0, const ICLTensor *input1, ICLTensor *output, const GEMMLHSMatrixInfo &lhs_info,
+                                                     const GEMMRHSMatrixInfo &rhs_info,
+                                                     const GEMMReshapeInfo   &gemm_info)
+{
     ARM_COMPUTE_ERROR_ON_NULLPTR(input0, input1, output);
 
     ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(input0->info(), input1->info(), output->info(), lhs_info, rhs_info, gemm_info));
@@ -223,7 +230,7 @@
     std::string kernel_name("gemmlowp_mm_native");
 
     // Create kernel
-    _kernel = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel(kernel_name, build_opts.options()));
+    _kernel = create_kernel(compile_context, kernel_name, build_opts.options());
 
     // Set config_id for enabling LWS tuning
     _config_id = kernel_name;
diff --git a/src/core/CL/kernels/CLGEMMLowpMatrixMultiplyReshapedKernel.cpp b/src/core/CL/kernels/CLGEMMLowpMatrixMultiplyReshapedKernel.cpp
index dd1f221..ebb00a4 100644
--- a/src/core/CL/kernels/CLGEMMLowpMatrixMultiplyReshapedKernel.cpp
+++ b/src/core/CL/kernels/CLGEMMLowpMatrixMultiplyReshapedKernel.cpp
@@ -168,6 +168,13 @@
 void CLGEMMLowpMatrixMultiplyReshapedKernel::configure(const ICLTensor *input0, const ICLTensor *input1, ICLTensor *output, const GEMMLHSMatrixInfo &lhs_info, const GEMMRHSMatrixInfo &rhs_info,
                                                        const GEMMReshapeInfo &gemm_info)
 {
+    configure(CLKernelLibrary::get().get_compile_context(), input0, input1, output, lhs_info, rhs_info, gemm_info);
+}
+
+void CLGEMMLowpMatrixMultiplyReshapedKernel::configure(CLCompileContext &compile_context, const ICLTensor *input0, const ICLTensor *input1, ICLTensor *output, const GEMMLHSMatrixInfo &lhs_info,
+                                                       const GEMMRHSMatrixInfo &rhs_info,
+                                                       const GEMMReshapeInfo   &gemm_info)
+{
     ARM_COMPUTE_ERROR_ON_NULLPTR(input0, input1, output);
 
     ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(input0->info(), input1->info(), output->info(), lhs_info, rhs_info, gemm_info));
@@ -214,7 +221,7 @@
     kernel_name += rhs_info.transpose ? "rhs_t" : "rhs_nt";
 
     // Create kernel
-    _kernel = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel(kernel_name, build_opts.options()));
+    _kernel = create_kernel(compile_context, kernel_name, build_opts.options());
 
     // Set config_id for enabling LWS tuning
     _config_id = kernel_name;
diff --git a/src/core/CL/kernels/CLGEMMLowpMatrixMultiplyReshapedOnlyRHSKernel.cpp b/src/core/CL/kernels/CLGEMMLowpMatrixMultiplyReshapedOnlyRHSKernel.cpp
index cef5b34..dd4c55c 100644
--- a/src/core/CL/kernels/CLGEMMLowpMatrixMultiplyReshapedOnlyRHSKernel.cpp
+++ b/src/core/CL/kernels/CLGEMMLowpMatrixMultiplyReshapedOnlyRHSKernel.cpp
@@ -310,6 +310,13 @@
                                                               const ICLTensor *vector_sum_col, const ICLTensor *vector_sum_row, const ICLTensor *bias,
                                                               const ICLTensor *output_multipliers, const ICLTensor *output_shifts)
 {
+    configure(CLKernelLibrary::get().get_compile_context(), input0, input1, output, gemm_info, vector_sum_col, vector_sum_row, bias, output_multipliers, output_shifts);
+}
+
+void CLGEMMLowpMatrixMultiplyReshapedOnlyRHSKernel::configure(CLCompileContext &compile_context, const ICLTensor *input0, const ICLTensor *input1, ICLTensor *output, const GEMMKernelInfo &gemm_info,
+                                                              const ICLTensor *vector_sum_col, const ICLTensor *vector_sum_row, const ICLTensor *bias,
+                                                              const ICLTensor *output_multipliers, const ICLTensor *output_shifts)
+{
     ARM_COMPUTE_ERROR_ON_NULLPTR(input0, input1, output);
     ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(input0->info(),
                                                   input1->info(),
@@ -420,7 +427,7 @@
     }
 
     // Create kernel
-    _kernel = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel(kernel_name, build_opts.options()));
+    _kernel = create_kernel(compile_context, kernel_name, build_opts.options());
 
     // Set config_id for enabling LWS tuning
     _config_id = kernel_name;
diff --git a/src/core/CL/kernels/CLGEMMLowpOffsetContributionKernel.cpp b/src/core/CL/kernels/CLGEMMLowpOffsetContributionKernel.cpp
index 49905fe..fd2cc7a 100644
--- a/src/core/CL/kernels/CLGEMMLowpOffsetContributionKernel.cpp
+++ b/src/core/CL/kernels/CLGEMMLowpOffsetContributionKernel.cpp
@@ -145,6 +145,13 @@
 void CLGEMMLowpOffsetContributionKernel::configure(ICLTensor *mm_result, const ICLTensor *vector_sum_col, const ICLTensor *vector_sum_row, const ICLTensor *bias, int32_t k, int32_t a_offset,
                                                    int32_t b_offset)
 {
+    configure(CLKernelLibrary::get().get_compile_context(), mm_result, vector_sum_col, vector_sum_row, bias, k, a_offset, b_offset);
+}
+
+void CLGEMMLowpOffsetContributionKernel::configure(CLCompileContext &compile_context, ICLTensor *mm_result, const ICLTensor *vector_sum_col, const ICLTensor *vector_sum_row, const ICLTensor *bias,
+                                                   int32_t k, int32_t a_offset,
+                                                   int32_t b_offset)
+{
     // Perform validate step
     ARM_COMPUTE_ERROR_ON_NULLPTR(mm_result);
     ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(mm_result->info(),
@@ -182,7 +189,7 @@
     std::string kernel_name("gemmlowp_offset_contribution");
 
     // Create kernel
-    _kernel = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel(kernel_name, build_opts.options()));
+    _kernel = create_kernel(compile_context, kernel_name, build_opts.options());
 
     // Configure kernel window
     auto win_config = validate_and_configure_window(mm_result->info(),
diff --git a/src/core/CL/kernels/CLGEMMLowpOffsetContributionOutputStageKernel.cpp b/src/core/CL/kernels/CLGEMMLowpOffsetContributionOutputStageKernel.cpp
index bae0a13..d52fb21 100644
--- a/src/core/CL/kernels/CLGEMMLowpOffsetContributionOutputStageKernel.cpp
+++ b/src/core/CL/kernels/CLGEMMLowpOffsetContributionOutputStageKernel.cpp
@@ -184,6 +184,14 @@
                                                               int32_t k, int32_t a_offset, int32_t b_offset, const GEMMLowpOutputStageInfo &output_stage,
                                                               const ICLTensor *output_multipliers, const ICLTensor *output_shifts)
 {
+    configure(CLKernelLibrary::get().get_compile_context(), mm_result, vector_sum_col, vector_sum_row, bias, output, k, a_offset, b_offset, output_stage, output_multipliers, output_shifts);
+}
+
+void CLGEMMLowpOffsetContributionOutputStageKernel::configure(CLCompileContext &compile_context, const ICLTensor *mm_result, const ICLTensor *vector_sum_col, const ICLTensor *vector_sum_row,
+                                                              const ICLTensor *bias, ICLTensor *output,
+                                                              int32_t k, int32_t a_offset, int32_t b_offset, const GEMMLowpOutputStageInfo &output_stage,
+                                                              const ICLTensor *output_multipliers, const ICLTensor *output_shifts)
+{
     // Perform validate step
     ARM_COMPUTE_ERROR_ON_NULLPTR(mm_result, output, output_multipliers, output_shifts);
     ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(mm_result->info(),
@@ -242,7 +250,7 @@
     kernel_name += "_" + string_from_gemmlowp_output_stage(output_stage.type);
 
     // Create kernel
-    _kernel = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel(kernel_name, build_opts.options()));
+    _kernel = create_kernel(compile_context, kernel_name, build_opts.options());
 
     // Configure kernel window
     auto win_config = validate_and_configure_window(mm_result->info(),
diff --git a/src/core/CL/kernels/CLGEMMLowpQuantizeDownInt32ScaleByFloatKernel.cpp b/src/core/CL/kernels/CLGEMMLowpQuantizeDownInt32ScaleByFloatKernel.cpp
index 5a554f3..171dc48 100644
--- a/src/core/CL/kernels/CLGEMMLowpQuantizeDownInt32ScaleByFloatKernel.cpp
+++ b/src/core/CL/kernels/CLGEMMLowpQuantizeDownInt32ScaleByFloatKernel.cpp
@@ -117,6 +117,12 @@
 void CLGEMMLowpQuantizeDownInt32ScaleByFloatKernel::configure(const ICLTensor *input, const ICLTensor *bias, ICLTensor *output,
                                                               const GEMMLowpOutputStageInfo *info)
 {
+    configure(CLKernelLibrary::get().get_compile_context(), input, bias, output, info);
+}
+
+void CLGEMMLowpQuantizeDownInt32ScaleByFloatKernel::configure(CLCompileContext &compile_context, const ICLTensor *input, const ICLTensor *bias, ICLTensor *output,
+                                                              const GEMMLowpOutputStageInfo *info)
+{
     // Perform validate step
     ARM_COMPUTE_ERROR_ON_NULLPTR(input, output);
     ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(input->info(), (bias != nullptr) ? bias->info() : nullptr, output->info(), info));
@@ -138,7 +144,7 @@
     build_opts.add_option_if(bias != nullptr, "-DADD_BIAS");
 
     // Create kernel
-    _kernel = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel("gemmlowp_output_stage_quantize_down_float", build_opts.options()));
+    _kernel = create_kernel(compile_context, "gemmlowp_output_stage_quantize_down_float", build_opts.options());
 
     // Configure kernel window
     auto win_config = validate_and_configure_window(input->info(), (bias != nullptr) ? bias->info() : nullptr, output->info(), info->output_data_type);
diff --git a/src/core/CL/kernels/CLGEMMLowpQuantizeDownInt32ScaleKernel.cpp b/src/core/CL/kernels/CLGEMMLowpQuantizeDownInt32ScaleKernel.cpp
index 002af6b..ca85e8b 100644
--- a/src/core/CL/kernels/CLGEMMLowpQuantizeDownInt32ScaleKernel.cpp
+++ b/src/core/CL/kernels/CLGEMMLowpQuantizeDownInt32ScaleKernel.cpp
@@ -107,6 +107,11 @@
 
 void CLGEMMLowpQuantizeDownInt32ScaleKernel::configure(const ICLTensor *input, const ICLTensor *bias, ICLTensor *output, const GEMMLowpOutputStageInfo *output_stage)
 {
+    configure(CLKernelLibrary::get().get_compile_context(), input, bias, output, output_stage);
+}
+
+void CLGEMMLowpQuantizeDownInt32ScaleKernel::configure(CLCompileContext &compile_context, const ICLTensor *input, const ICLTensor *bias, ICLTensor *output, const GEMMLowpOutputStageInfo *output_stage)
+{
     // Perform validate step
     ARM_COMPUTE_ERROR_ON_NULLPTR(input, output);
 
@@ -135,7 +140,7 @@
     build_opts.add_option_if(bias != nullptr, "-DADD_BIAS");
 
     // Create kernel
-    _kernel = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel("gemmlowp_output_stage_quantize_down", build_opts.options()));
+    _kernel = create_kernel(compile_context, "gemmlowp_output_stage_quantize_down", build_opts.options());
 
     // Configure kernel window
     auto win_config = validate_and_configure_window(input->info(), (bias != nullptr) ? bias->info() : nullptr, output->info(), output_stage->output_data_type);
diff --git a/src/core/CL/kernels/CLGEMMLowpQuantizeDownInt32ToInt16ScaleByFixedPointKernel.cpp b/src/core/CL/kernels/CLGEMMLowpQuantizeDownInt32ToInt16ScaleByFixedPointKernel.cpp
index 22300b9..00cef56 100644
--- a/src/core/CL/kernels/CLGEMMLowpQuantizeDownInt32ToInt16ScaleByFixedPointKernel.cpp
+++ b/src/core/CL/kernels/CLGEMMLowpQuantizeDownInt32ToInt16ScaleByFixedPointKernel.cpp
@@ -123,6 +123,13 @@
                                                                           int result_fixedpoint_multiplier, int result_shift,
                                                                           int min, int max)
 {
+    configure(CLKernelLibrary::get().get_compile_context(), input, bias, output, result_fixedpoint_multiplier, result_shift, min, max);
+}
+
+void CLGEMMLowpQuantizeDownInt32ToInt16ScaleByFixedPointKernel::configure(CLCompileContext &compile_context, const ICLTensor *input, const ICLTensor *bias, ICLTensor *output,
+                                                                          int result_fixedpoint_multiplier, int result_shift,
+                                                                          int min, int max)
+{
     // Perform validate step
     ARM_COMPUTE_ERROR_ON_NULLPTR(input, output);
     ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(input->info(), (bias != nullptr) ? bias->info() : nullptr, output->info(),
@@ -141,7 +148,7 @@
     build_opts.add_option_if(bias != nullptr, "-DADD_BIAS");
 
     // Create kernel
-    _kernel = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel("gemmlowp_output_stage_quantize_down_fixedpoint_qsymm16", build_opts.options()));
+    _kernel = create_kernel(compile_context, "gemmlowp_output_stage_quantize_down_fixedpoint_qsymm16", build_opts.options());
 
     // Configure kernel window
     auto win_config = validate_and_configure_window(input->info(), (bias != nullptr) ? bias->info() : nullptr, output->info());
diff --git a/src/core/CL/kernels/CLGEMMLowpQuantizeDownInt32ToInt8ScaleByFixedPointKernel.cpp b/src/core/CL/kernels/CLGEMMLowpQuantizeDownInt32ToInt8ScaleByFixedPointKernel.cpp
index 9e0570a..b6d98e6 100644
--- a/src/core/CL/kernels/CLGEMMLowpQuantizeDownInt32ToInt8ScaleByFixedPointKernel.cpp
+++ b/src/core/CL/kernels/CLGEMMLowpQuantizeDownInt32ToInt8ScaleByFixedPointKernel.cpp
@@ -118,6 +118,13 @@
                                                                          int result_fixedpoint_multiplier, int result_shift, int result_offset_after_shift,
                                                                          int min, int max)
 {
+    configure(CLKernelLibrary::get().get_compile_context(), input, bias, output, result_fixedpoint_multiplier, result_shift, result_offset_after_shift, min, max);
+}
+
+void CLGEMMLowpQuantizeDownInt32ToInt8ScaleByFixedPointKernel::configure(CLCompileContext &compile_context, const ICLTensor *input, const ICLTensor *bias, ICLTensor *output,
+                                                                         int result_fixedpoint_multiplier, int result_shift, int result_offset_after_shift,
+                                                                         int min, int max)
+{
     // Perform validate step
     ARM_COMPUTE_ERROR_ON_NULLPTR(input, output);
     ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(input->info(), (bias != nullptr) ? bias->info() : nullptr, output->info(), min, max));
@@ -140,7 +147,7 @@
     build_opts.add_option_if(bias != nullptr, "-DADD_BIAS");
 
     // Create kernel
-    _kernel = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel("gemmlowp_output_stage_quantize_down_fixedpoint", build_opts.options()));
+    _kernel = create_kernel(compile_context, "gemmlowp_output_stage_quantize_down_fixedpoint", build_opts.options());
 
     ICLKernel::configure_internal(win_config.second);
 }
diff --git a/src/core/CL/kernels/CLGEMMLowpQuantizeDownInt32ToUint8ScaleByFixedPointKernel.cpp b/src/core/CL/kernels/CLGEMMLowpQuantizeDownInt32ToUint8ScaleByFixedPointKernel.cpp
index 6ab3272..7f2f2e7 100644
--- a/src/core/CL/kernels/CLGEMMLowpQuantizeDownInt32ToUint8ScaleByFixedPointKernel.cpp
+++ b/src/core/CL/kernels/CLGEMMLowpQuantizeDownInt32ToUint8ScaleByFixedPointKernel.cpp
@@ -118,6 +118,13 @@
                                                                           int result_fixedpoint_multiplier, int result_shift, int result_offset_after_shift,
                                                                           int min, int max)
 {
+    configure(CLKernelLibrary::get().get_compile_context(), input, bias, output, result_fixedpoint_multiplier, result_shift, result_offset_after_shift, min, max);
+}
+
+void CLGEMMLowpQuantizeDownInt32ToUint8ScaleByFixedPointKernel::configure(CLCompileContext &compile_context, const ICLTensor *input, const ICLTensor *bias, ICLTensor *output,
+                                                                          int result_fixedpoint_multiplier, int result_shift, int result_offset_after_shift,
+                                                                          int min, int max)
+{
     // Perform validate step
     ARM_COMPUTE_ERROR_ON_NULLPTR(input, output);
     ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(input->info(), (bias != nullptr) ? bias->info() : nullptr, output->info(), min, max));
@@ -140,7 +147,7 @@
     build_opts.add_option_if(bias != nullptr, "-DADD_BIAS");
 
     // Create kernel
-    _kernel = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel("gemmlowp_output_stage_quantize_down_fixedpoint", build_opts.options()));
+    _kernel = create_kernel(compile_context, "gemmlowp_output_stage_quantize_down_fixedpoint", build_opts.options());
 
     ICLKernel::configure_internal(win_config.second);
 }
diff --git a/src/core/CL/kernels/CLGEMMLowpReductionKernel.cpp b/src/core/CL/kernels/CLGEMMLowpReductionKernel.cpp
index 832e628..e81ab2f 100644
--- a/src/core/CL/kernels/CLGEMMLowpReductionKernel.cpp
+++ b/src/core/CL/kernels/CLGEMMLowpReductionKernel.cpp
@@ -85,6 +85,11 @@
 
 void CLGEMMLowpMatrixAReductionKernel::configure(const ICLTensor *mtx_a, ICLTensor *vector_sum_row, const GEMMLowpReductionKernelInfo &info)
 {
+    configure(CLKernelLibrary::get().get_compile_context(), mtx_a, vector_sum_row, info);
+}
+
+void CLGEMMLowpMatrixAReductionKernel::configure(CLCompileContext &compile_context, const ICLTensor *mtx_a, ICLTensor *vector_sum_row, const GEMMLowpReductionKernelInfo &info)
+{
     // Perform validate step
     ARM_COMPUTE_ERROR_ON_NULLPTR(mtx_a, vector_sum_row);
     ARM_COMPUTE_ERROR_THROW_ON(validate_arguments_matrix_a_reduction(mtx_a->info(), vector_sum_row->info()));
@@ -104,7 +109,7 @@
     std::string kernel_name = "gemmlowp_matrix_a_reduction" + std::string(is_dot8_supported ? "_dot8" : "");
 
     // Create kernel
-    _kernel = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel(kernel_name, build_opts.options()));
+    _kernel = create_kernel(compile_context, kernel_name, build_opts.options());
 
     // Configure kernel window
     // This kernel does not need padding
@@ -154,6 +159,11 @@
 
 void CLGEMMLowpMatrixBReductionKernel::configure(const ICLTensor *mtx_b, ICLTensor *vector_sum_col, const GEMMLowpReductionKernelInfo &info)
 {
+    configure(CLKernelLibrary::get().get_compile_context(), mtx_b, vector_sum_col, info);
+}
+
+void CLGEMMLowpMatrixBReductionKernel::configure(CLCompileContext &compile_context, const ICLTensor *mtx_b, ICLTensor *vector_sum_col, const GEMMLowpReductionKernelInfo &info)
+{
     ARM_COMPUTE_ERROR_ON_NULLPTR(mtx_b, vector_sum_col);
     ARM_COMPUTE_ERROR_THROW_ON(validate_arguments_matrix_b_reduction(mtx_b->info(), vector_sum_col->info()));
 
@@ -169,7 +179,7 @@
     build_opts.add_option_if(info.mul_by_scalar, "-DSCALAR=" + support::cpp11::to_string(info.scalar));
 
     // Create kernel
-    _kernel = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel("gemmlowp_matrix_b_reduction", build_opts.options()));
+    _kernel = create_kernel(compile_context, "gemmlowp_matrix_b_reduction", build_opts.options());
 
     // Configure kernel window
     auto win_config = validate_and_configure_window_matrix_b_reduction(_input->info(), _output->info());
diff --git a/src/core/CL/kernels/CLGEMMMatrixAccumulateBiasesKernel.cpp b/src/core/CL/kernels/CLGEMMMatrixAccumulateBiasesKernel.cpp
index 806afb4..045ae28 100644
--- a/src/core/CL/kernels/CLGEMMMatrixAccumulateBiasesKernel.cpp
+++ b/src/core/CL/kernels/CLGEMMMatrixAccumulateBiasesKernel.cpp
@@ -79,6 +79,11 @@
 
 void CLGEMMMatrixAccumulateBiasesKernel::configure(ICLTensor *accum, const ICLTensor *biases)
 {
+    configure(CLKernelLibrary::get().get_compile_context(), accum, biases);
+}
+
+void CLGEMMMatrixAccumulateBiasesKernel::configure(CLCompileContext &compile_context, ICLTensor *accum, const ICLTensor *biases)
+{
     // Perform validate step
     ARM_COMPUTE_ERROR_ON_NULLPTR(accum, biases);
     ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(accum->info(), biases->info()));
@@ -101,7 +106,7 @@
     build_opts.add_option("-DVECTOR_SIZE=" + support::cpp11::to_string(vector_size));
 
     // Create kernel
-    _kernel = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel("gemm_accumulate_biases", build_opts.options()));
+    _kernel = create_kernel(compile_context, "gemm_accumulate_biases", build_opts.options());
 }
 
 Status CLGEMMMatrixAccumulateBiasesKernel::validate(const ITensorInfo *accum, const ITensorInfo *biases, GPUTarget gpu_target)
diff --git a/src/core/CL/kernels/CLGEMMMatrixMultiplyKernel.cpp b/src/core/CL/kernels/CLGEMMMatrixMultiplyKernel.cpp
index 8e76403..9587a04 100644
--- a/src/core/CL/kernels/CLGEMMMatrixMultiplyKernel.cpp
+++ b/src/core/CL/kernels/CLGEMMMatrixMultiplyKernel.cpp
@@ -307,6 +307,12 @@
 void CLGEMMMatrixMultiplyKernel::configure(const ICLTensor *input0, const ICLTensor *input1, const ICLTensor *input2, ICLTensor *output, float alpha, float beta,
                                            bool is_interleaved_transposed, const GEMMReshapeInfo &reshape_info, bool fp_mixed_precision, const ActivationLayerInfo &activation_info)
 {
+    configure(CLKernelLibrary::get().get_compile_context(), input0, input1, input2, output, alpha, beta, is_interleaved_transposed, reshape_info, fp_mixed_precision, activation_info);
+}
+
+void CLGEMMMatrixMultiplyKernel::configure(CLCompileContext &compile_context, const ICLTensor *input0, const ICLTensor *input1, const ICLTensor *input2, ICLTensor *output, float alpha, float beta,
+                                           bool is_interleaved_transposed, const GEMMReshapeInfo &reshape_info, bool fp_mixed_precision, const ActivationLayerInfo &activation_info)
+{
     ARM_COMPUTE_ERROR_ON_NULLPTR(input0, input1, output);
 
     // Perform validate step
@@ -430,7 +436,7 @@
     }
 
     // Create kernel
-    _kernel = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel(kernel_name, build_opts.options()));
+    _kernel = create_kernel(compile_context, kernel_name, build_opts.options());
 
     // Set config_id for enabling LWS tuning
     _config_id = "gemm_";
diff --git a/src/core/CL/kernels/CLGEMMMatrixMultiplyNativeKernel.cpp b/src/core/CL/kernels/CLGEMMMatrixMultiplyNativeKernel.cpp
index d150391..af4b097 100644
--- a/src/core/CL/kernels/CLGEMMMatrixMultiplyNativeKernel.cpp
+++ b/src/core/CL/kernels/CLGEMMMatrixMultiplyNativeKernel.cpp
@@ -214,6 +214,14 @@
                                                  const GEMMLHSMatrixInfo &lhs_info,
                                                  const GEMMRHSMatrixInfo &rhs_info, const GEMMKernelInfo &gemm_info)
 {
+    configure(CLKernelLibrary::get().get_compile_context(), input0, input1, input2, output, alpha, beta, lhs_info, rhs_info, gemm_info);
+}
+
+void CLGEMMMatrixMultiplyNativeKernel::configure(CLCompileContext &compile_context, const ICLTensor *input0, const ICLTensor *input1, const ICLTensor *input2, ICLTensor *output, float alpha,
+                                                 float                    beta,
+                                                 const GEMMLHSMatrixInfo &lhs_info,
+                                                 const GEMMRHSMatrixInfo &rhs_info, const GEMMKernelInfo &gemm_info)
+{
     ARM_COMPUTE_ERROR_ON_NULLPTR(input0, input1, output);
 
     ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(input0->info(), input1->info(), (input2 != nullptr ? input2->info() : nullptr), output->info(), alpha, beta, lhs_info, rhs_info, gemm_info));
@@ -281,7 +289,7 @@
     std::string kernel_name("gemm_mm_native");
 
     // Create kernel
-    _kernel = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel(kernel_name, build_opts.options()));
+    _kernel = create_kernel(compile_context, kernel_name, build_opts.options());
 
     // Set config_id for enabling LWS tuning
     _config_id = kernel_name;
diff --git a/src/core/CL/kernels/CLGEMMMatrixMultiplyReshapedKernel.cpp b/src/core/CL/kernels/CLGEMMMatrixMultiplyReshapedKernel.cpp
index 3f154a5..eb01486 100644
--- a/src/core/CL/kernels/CLGEMMMatrixMultiplyReshapedKernel.cpp
+++ b/src/core/CL/kernels/CLGEMMMatrixMultiplyReshapedKernel.cpp
@@ -216,6 +216,14 @@
                                                    const GEMMLHSMatrixInfo &lhs_info,
                                                    const GEMMRHSMatrixInfo &rhs_info, const GEMMKernelInfo &gemm_info)
 {
+    configure(CLKernelLibrary::get().get_compile_context(), input0, input1, input2, output, alpha, beta, lhs_info, rhs_info, gemm_info);
+}
+
+void CLGEMMMatrixMultiplyReshapedKernel::configure(CLCompileContext &compile_context, const ICLTensor *input0, const ICLTensor *input1, const ICLTensor *input2, ICLTensor *output, float alpha,
+                                                   float                    beta,
+                                                   const GEMMLHSMatrixInfo &lhs_info,
+                                                   const GEMMRHSMatrixInfo &rhs_info, const GEMMKernelInfo &gemm_info)
+{
     ARM_COMPUTE_ERROR_ON_NULLPTR(input0, input1, output);
 
     ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(input0->info(), input1->info(), (input2 != nullptr ? input2->info() : nullptr), output->info(), alpha, beta, lhs_info, rhs_info, gemm_info));
@@ -277,7 +285,7 @@
     kernel_name += rhs_info.transpose ? "rhs_t" : "rhs_nt";
 
     // Create kernel
-    _kernel = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel(kernel_name, build_opts.options()));
+    _kernel = create_kernel(compile_context, kernel_name, build_opts.options());
 
     // Set config_id for enabling LWS tuning
     _config_id = kernel_name;
diff --git a/src/core/CL/kernels/CLGEMMMatrixMultiplyReshapedOnlyRHSKernel.cpp b/src/core/CL/kernels/CLGEMMMatrixMultiplyReshapedOnlyRHSKernel.cpp
index ed66997..011e93d 100644
--- a/src/core/CL/kernels/CLGEMMMatrixMultiplyReshapedOnlyRHSKernel.cpp
+++ b/src/core/CL/kernels/CLGEMMMatrixMultiplyReshapedOnlyRHSKernel.cpp
@@ -217,6 +217,14 @@
                                                           const GEMMLHSMatrixInfo &lhs_info,
                                                           const GEMMRHSMatrixInfo &rhs_info, const GEMMKernelInfo &gemm_info)
 {
+    configure(CLKernelLibrary::get().get_compile_context(), input0, input1, input2, output, alpha, beta, lhs_info, rhs_info, gemm_info);
+}
+
+void CLGEMMMatrixMultiplyReshapedOnlyRHSKernel::configure(CLCompileContext &compile_context, const ICLTensor *input0, const ICLTensor *input1, const ICLTensor *input2, ICLTensor *output, float alpha,
+                                                          float                    beta,
+                                                          const GEMMLHSMatrixInfo &lhs_info,
+                                                          const GEMMRHSMatrixInfo &rhs_info, const GEMMKernelInfo &gemm_info)
+{
     ARM_COMPUTE_ERROR_ON_NULLPTR(input0, input1, output);
 
     ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(input0->info(), input1->info(), (input2 != nullptr ? input2->info() : nullptr), output->info(), alpha, beta, lhs_info, rhs_info, gemm_info));
@@ -287,7 +295,7 @@
     kernel_name += rhs_info.transpose ? "t" : "nt";
 
     // Create kernel
-    _kernel = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel(kernel_name, build_opts.options()));
+    _kernel = create_kernel(compile_context, kernel_name, build_opts.options());
 
     // Set config_id for enabling LWS tuning
     _config_id = kernel_name;
diff --git a/src/core/CL/kernels/CLGEMMMatrixVectorMultiplyKernel.cpp b/src/core/CL/kernels/CLGEMMMatrixVectorMultiplyKernel.cpp
index 03889bd..98a1dee 100644
--- a/src/core/CL/kernels/CLGEMMMatrixVectorMultiplyKernel.cpp
+++ b/src/core/CL/kernels/CLGEMMMatrixVectorMultiplyKernel.cpp
@@ -83,6 +83,11 @@
 
 void CLGEMMMatrixVectorMultiplyKernel::configure(const ICLTensor *input0, const ICLTensor *input1, ICLTensor *output)
 {
+    configure(CLKernelLibrary::get().get_compile_context(), input0, input1, output);
+}
+
+void CLGEMMMatrixVectorMultiplyKernel::configure(CLCompileContext &compile_context, const ICLTensor *input0, const ICLTensor *input1, ICLTensor *output)
+{
     ARM_COMPUTE_ERROR_ON_NULLPTR(input0, input1, output);
     ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(input0->info(), input1->info(), output->info()));
 
@@ -100,7 +105,7 @@
     build_opts.add_option("-DSRC_HEIGHT=" + support::cpp11::to_string(input0->info()->dimension(1)));
 
     std::string kernel_name = is_quantized ? std::string("gemm_mv_quantized") : std::string("gemm_mv");
-    _kernel                 = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel(kernel_name, build_opts.options()));
+    _kernel                 = create_kernel(compile_context, kernel_name, build_opts.options());
 
     // Add static arguments
     if(is_quantized)
diff --git a/src/core/CL/kernels/CLGEMMReshapeLHSMatrixKernel.cpp b/src/core/CL/kernels/CLGEMMReshapeLHSMatrixKernel.cpp
index 6f92522..73e3106 100644
--- a/src/core/CL/kernels/CLGEMMReshapeLHSMatrixKernel.cpp
+++ b/src/core/CL/kernels/CLGEMMReshapeLHSMatrixKernel.cpp
@@ -121,6 +121,11 @@
 
 void CLGEMMReshapeLHSMatrixKernel::configure(const ICLTensor *input, ICLTensor *output, const GEMMLHSMatrixInfo &lhs_info, bool reinterpret_input_as_3d)
 {
+    configure(CLKernelLibrary::get().get_compile_context(), input, output, lhs_info, reinterpret_input_as_3d);
+}
+
+void CLGEMMReshapeLHSMatrixKernel::configure(CLCompileContext &compile_context, const ICLTensor *input, ICLTensor *output, const GEMMLHSMatrixInfo &lhs_info, bool reinterpret_input_as_3d)
+{
     ARM_COMPUTE_ERROR_ON_NULLPTR(input, output);
 
     // Perform validate step
@@ -146,7 +151,7 @@
     kernel_name += lhs_info.transpose ? "t" : "nt";
 
     // Create kernel
-    _kernel = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel(kernel_name, build_opts.options()));
+    _kernel = create_kernel(compile_context, kernel_name, build_opts.options());
 
     // Configure kernel window
     auto win_config = validate_and_configure_window(input->info(), output->info(), lhs_info, reinterpret_input_as_3d);
diff --git a/src/core/CL/kernels/CLGEMMReshapeRHSMatrixKernel.cpp b/src/core/CL/kernels/CLGEMMReshapeRHSMatrixKernel.cpp
index 766b3e6..1623b1e5 100644
--- a/src/core/CL/kernels/CLGEMMReshapeRHSMatrixKernel.cpp
+++ b/src/core/CL/kernels/CLGEMMReshapeRHSMatrixKernel.cpp
@@ -102,6 +102,11 @@
 
 void CLGEMMReshapeRHSMatrixKernel::configure(const ICLTensor *input, ICLTensor *output, const GEMMRHSMatrixInfo &rhs_info)
 {
+    configure(CLKernelLibrary::get().get_compile_context(), input, output, rhs_info);
+}
+
+void CLGEMMReshapeRHSMatrixKernel::configure(CLCompileContext &compile_context, const ICLTensor *input, ICLTensor *output, const GEMMRHSMatrixInfo &rhs_info)
+{
     ARM_COMPUTE_ERROR_ON_NULLPTR(input, output);
 
     // Perform validate step
@@ -124,7 +129,7 @@
     kernel_name += rhs_info.transpose ? "t" : "nt";
 
     // Create kernel
-    _kernel = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel(kernel_name, build_opts.options()));
+    _kernel = create_kernel(compile_context, kernel_name, build_opts.options());
 
     // Configure kernel window
     auto win_config = validate_and_configure_window(input->info(), output->info(), rhs_info);
diff --git a/src/core/CL/kernels/CLGatherKernel.cpp b/src/core/CL/kernels/CLGatherKernel.cpp
index ae77945..6bee66a 100644
--- a/src/core/CL/kernels/CLGatherKernel.cpp
+++ b/src/core/CL/kernels/CLGatherKernel.cpp
@@ -89,6 +89,11 @@
 
 void CLGatherKernel::configure(const ICLTensor *input, const ICLTensor *indices, ICLTensor *output, int axis)
 {
+    configure(CLKernelLibrary::get().get_compile_context(), input, indices, output, axis);
+}
+
+void CLGatherKernel::configure(CLCompileContext &compile_context, const ICLTensor *input, const ICLTensor *indices, ICLTensor *output, int axis)
+{
     ARM_COMPUTE_ERROR_ON_NULLPTR(input, output, indices);
     ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(input->info(), indices->info(), output->info(), axis));
 
@@ -109,7 +114,7 @@
     build_opts.add_option("-DAXIS=" + support::cpp11::to_string(_axis));
 
     // Create kernel
-    _kernel = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel("gather", build_opts.options()));
+    _kernel = create_kernel(compile_context, "gather", build_opts.options());
     ICLKernel::configure_internal(win_config.second);
 }
 
diff --git a/src/core/CL/kernels/CLGaussian3x3Kernel.cpp b/src/core/CL/kernels/CLGaussian3x3Kernel.cpp
index 7e8f313..0edf46b 100644
--- a/src/core/CL/kernels/CLGaussian3x3Kernel.cpp
+++ b/src/core/CL/kernels/CLGaussian3x3Kernel.cpp
@@ -1,5 +1,5 @@
 /*
- * Copyright (c) 2016-2018 ARM Limited.
+ * Copyright (c) 2016-2020 ARM Limited.
  *
  * SPDX-License-Identifier: MIT
  *
@@ -41,6 +41,11 @@
 
 void CLGaussian3x3Kernel::configure(const ICLTensor *input, ICLTensor *output, bool border_undefined)
 {
+    configure(CLKernelLibrary::get().get_compile_context(), input, output, border_undefined);
+}
+
+void CLGaussian3x3Kernel::configure(CLCompileContext &compile_context, const ICLTensor *input, ICLTensor *output, bool border_undefined)
+{
     ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::U8);
     ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(output, 1, DataType::U8);
 
@@ -55,7 +60,7 @@
                                        };
 
     // Create kernel
-    _kernel = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel("convolution3x3_static", build_opts));
+    _kernel = create_kernel(compile_context, "convolution3x3_static", build_opts);
 
     // Configure kernel window
     constexpr unsigned int num_elems_processed_per_iteration = 8;
diff --git a/src/core/CL/kernels/CLGaussian5x5Kernel.cpp b/src/core/CL/kernels/CLGaussian5x5Kernel.cpp
index 3b45b07..98436b9 100644
--- a/src/core/CL/kernels/CLGaussian5x5Kernel.cpp
+++ b/src/core/CL/kernels/CLGaussian5x5Kernel.cpp
@@ -1,5 +1,5 @@
 /*
- * Copyright (c) 2016-2019 ARM Limited.
+ * Copyright (c) 2016-2020 ARM Limited.
  *
  * SPDX-License-Identifier: MIT
  *
@@ -29,17 +29,27 @@
 
 void CLGaussian5x5HorKernel::configure(const ICLTensor *input, ICLTensor *output, bool border_undefined)
 {
+    configure(CLKernelLibrary::get().get_compile_context(), input, output, border_undefined);
+}
+
+void CLGaussian5x5HorKernel::configure(CLCompileContext &compile_context, const ICLTensor *input, ICLTensor *output, bool border_undefined)
+{
     const std::array<int16_t, 5> matrix = { 1, 4, 6, 4, 1 };
 
     // Set arguments
-    CLSeparableConvolution5x5HorKernel::configure(input, output, matrix.data(), border_undefined);
+    CLSeparableConvolution5x5HorKernel::configure(compile_context, input, output, matrix.data(), border_undefined);
 }
 
 void CLGaussian5x5VertKernel::configure(const ICLTensor *input, ICLTensor *output, bool border_undefined)
 {
+    configure(CLKernelLibrary::get().get_compile_context(), input, output, border_undefined);
+}
+
+void CLGaussian5x5VertKernel::configure(CLCompileContext &compile_context, const ICLTensor *input, ICLTensor *output, bool border_undefined)
+{
     const uint32_t scale = 256;
     const std::array<int16_t, 5> matrix = { 1, 4, 6, 4, 1 };
 
     // Set arguments
-    CLSeparableConvolution5x5VertKernel::configure(input, output, matrix.data(), scale, border_undefined);
+    CLSeparableConvolution5x5VertKernel::configure(compile_context, input, output, matrix.data(), scale, border_undefined);
 }
diff --git a/src/core/CL/kernels/CLGaussianPyramidKernel.cpp b/src/core/CL/kernels/CLGaussianPyramidKernel.cpp
index fd21bb6..8486d45 100644
--- a/src/core/CL/kernels/CLGaussianPyramidKernel.cpp
+++ b/src/core/CL/kernels/CLGaussianPyramidKernel.cpp
@@ -44,6 +44,11 @@
 
 void CLGaussianPyramidHorKernel::configure(const ICLTensor *input, ICLTensor *output)
 {
+    configure(CLKernelLibrary::get().get_compile_context(), input, output);
+}
+
+void CLGaussianPyramidHorKernel::configure(CLCompileContext &compile_context, const ICLTensor *input, ICLTensor *output)
+{
     ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::U8);
     ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(output, 1, DataType::U16);
     ARM_COMPUTE_ERROR_ON(input->info()->dimension(1) != output->info()->dimension(1));
@@ -58,7 +63,7 @@
 
     // Create kernel
     const std::string kernel_name = std::string("gaussian1x5_sub_x");
-    _kernel                       = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel(kernel_name));
+    _kernel                       = create_kernel(compile_context, kernel_name);
 
     // Configure kernel window
     constexpr unsigned int num_elems_processed_per_iteration = 16;
@@ -150,6 +155,11 @@
 
 void CLGaussianPyramidVertKernel::configure(const ICLTensor *input, ICLTensor *output)
 {
+    configure(CLKernelLibrary::get().get_compile_context(), input, output);
+}
+
+void CLGaussianPyramidVertKernel::configure(CLCompileContext &compile_context, const ICLTensor *input, ICLTensor *output)
+{
     ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::U16);
     ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(output, 1, DataType::U8);
     ARM_COMPUTE_ERROR_ON(input->info()->dimension(0) != output->info()->dimension(0));
@@ -164,7 +174,7 @@
 
     // Create kernel
     const std::string kernel_name = std::string("gaussian5x1_sub_y");
-    _kernel                       = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel("gaussian5x1_sub_y"));
+    _kernel                       = create_kernel(compile_context, "gaussian5x1_sub_y");
 
     // Configure kernel window
     constexpr unsigned int num_elems_processed_per_iteration = 8;
diff --git a/src/core/CL/kernels/CLGenerateProposalsLayerKernel.cpp b/src/core/CL/kernels/CLGenerateProposalsLayerKernel.cpp
index 96e2213..0f09152 100644
--- a/src/core/CL/kernels/CLGenerateProposalsLayerKernel.cpp
+++ b/src/core/CL/kernels/CLGenerateProposalsLayerKernel.cpp
@@ -73,6 +73,11 @@
 
 void CLComputeAllAnchorsKernel::configure(const ICLTensor *anchors, ICLTensor *all_anchors, const ComputeAnchorsInfo &info)
 {
+    configure(CLKernelLibrary::get().get_compile_context(), anchors, all_anchors, info);
+}
+
+void CLComputeAllAnchorsKernel::configure(CLCompileContext &compile_context, const ICLTensor *anchors, ICLTensor *all_anchors, const ComputeAnchorsInfo &info)
+{
     ARM_COMPUTE_ERROR_ON_NULLPTR(anchors, all_anchors);
     ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(anchors->info(), all_anchors->info(), info));
 
@@ -110,7 +115,7 @@
 
     // Create kernel
     const std::string kernel_name = (is_quantized) ? "generate_proposals_compute_all_anchors_quantized" : "generate_proposals_compute_all_anchors";
-    _kernel                       = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel(kernel_name, build_opts.options()));
+    _kernel                       = create_kernel(compile_context, kernel_name, build_opts.options());
 
     // The tensor all_anchors can be interpreted as an array of structs (each structs has values_per_roi fields).
     // This means we don't need to pad on the X dimension, as we know in advance how many fields
diff --git a/src/core/CL/kernels/CLHOGDescriptorKernel.cpp b/src/core/CL/kernels/CLHOGDescriptorKernel.cpp
index c251dec..f79388e 100644
--- a/src/core/CL/kernels/CLHOGDescriptorKernel.cpp
+++ b/src/core/CL/kernels/CLHOGDescriptorKernel.cpp
@@ -48,6 +48,11 @@
 
 void CLHOGOrientationBinningKernel::configure(const ICLTensor *input_magnitude, const ICLTensor *input_phase, ICLTensor *output, const HOGInfo *hog_info)
 {
+    configure(CLKernelLibrary::get().get_compile_context(), input_magnitude, input_phase, output, hog_info);
+}
+
+void CLHOGOrientationBinningKernel::configure(CLCompileContext &compile_context, const ICLTensor *input_magnitude, const ICLTensor *input_phase, ICLTensor *output, const HOGInfo *hog_info)
+{
     ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input_magnitude, 1, DataType::S16);
     ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input_phase, 1, DataType::U8);
     ARM_COMPUTE_ERROR_ON(hog_info == nullptr);
@@ -75,7 +80,7 @@
 
     // Create kernel
     const std::string kernel_name = std::string("hog_orientation_binning");
-    _kernel                       = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel(kernel_name, build_opts));
+    _kernel                       = create_kernel(compile_context, kernel_name, build_opts);
 
     constexpr unsigned int num_elems_processed_per_iteration = 1;
     constexpr unsigned int num_elems_read_per_iteration      = 1;
@@ -139,6 +144,11 @@
 
 void CLHOGBlockNormalizationKernel::configure(const ICLTensor *input, ICLTensor *output, const HOGInfo *hog_info)
 {
+    configure(CLKernelLibrary::get().get_compile_context(), input, output, hog_info);
+}
+
+void CLHOGBlockNormalizationKernel::configure(CLCompileContext &compile_context, const ICLTensor *input, ICLTensor *output, const HOGInfo *hog_info)
+{
     ARM_COMPUTE_ERROR_ON(hog_info == nullptr);
     ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, hog_info->num_bins(), DataType::F32);
     ARM_COMPUTE_ERROR_ON_DATA_TYPE_NOT_IN(output, DataType::F32);
@@ -172,7 +182,7 @@
     build_opts.insert(args_str.str());
 
     const std::string kernel_name = std::string("hog_block_normalization");
-    _kernel                       = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel(kernel_name, build_opts));
+    _kernel                       = create_kernel(compile_context, kernel_name, build_opts);
 
     constexpr unsigned int num_elems_processed_per_iteration = 1;
     constexpr unsigned int num_elems_read_per_iteration      = 1;
diff --git a/src/core/CL/kernels/CLHOGDetectorKernel.cpp b/src/core/CL/kernels/CLHOGDetectorKernel.cpp
index c003df4..02fad20 100644
--- a/src/core/CL/kernels/CLHOGDetectorKernel.cpp
+++ b/src/core/CL/kernels/CLHOGDetectorKernel.cpp
@@ -45,6 +45,13 @@
 void CLHOGDetectorKernel::configure(const ICLTensor *input, const ICLHOG *hog, ICLDetectionWindowArray *detection_windows, cl::Buffer *num_detection_windows, const Size2D &detection_window_stride,
                                     float threshold, uint16_t idx_class)
 {
+    configure(CLKernelLibrary::get().get_compile_context(), input, hog, detection_windows, num_detection_windows, detection_window_stride, threshold, idx_class);
+}
+
+void CLHOGDetectorKernel::configure(CLCompileContext &compile_context, const ICLTensor *input, const ICLHOG *hog, ICLDetectionWindowArray *detection_windows, cl::Buffer *num_detection_windows,
+                                    const Size2D &detection_window_stride,
+                                    float threshold, uint16_t idx_class)
+{
     ARM_COMPUTE_ERROR_ON_DATA_TYPE_NOT_IN(input, DataType::F32);
     ARM_COMPUTE_ERROR_ON(hog == nullptr);
     ARM_COMPUTE_ERROR_ON(detection_windows == nullptr);
@@ -82,7 +89,7 @@
 
     // Create kernel
     const std::string kernel_name = std::string("hog_detector");
-    _kernel                       = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel(kernel_name, build_opts));
+    _kernel                       = create_kernel(compile_context, kernel_name, build_opts);
 
     // Set static kernel arguments
     unsigned int idx = num_arguments_per_2D_tensor(); // Skip the input parameters
diff --git a/src/core/CL/kernels/CLHarrisCornersKernel.cpp b/src/core/CL/kernels/CLHarrisCornersKernel.cpp
index eb1ebf6..2c344c7 100644
--- a/src/core/CL/kernels/CLHarrisCornersKernel.cpp
+++ b/src/core/CL/kernels/CLHarrisCornersKernel.cpp
@@ -56,6 +56,13 @@
                                     int32_t block_size, float norm_factor, float strength_thresh, float sensitivity,
                                     bool border_undefined)
 {
+    configure(CLKernelLibrary::get().get_compile_context(), input1, input2, output, block_size, norm_factor, strength_thresh, sensitivity, border_undefined);
+}
+
+void CLHarrisScoreKernel::configure(CLCompileContext &compile_context, const ICLImage *input1, const ICLImage *input2, ICLImage *output,
+                                    int32_t block_size, float norm_factor, float strength_thresh, float sensitivity,
+                                    bool border_undefined)
+{
     ARM_COMPUTE_ERROR_ON_TENSOR_NOT_2D(input1);
     ARM_COMPUTE_ERROR_ON_TENSOR_NOT_2D(input2);
     ARM_COMPUTE_ERROR_ON_TENSOR_NOT_2D(output);
@@ -82,7 +89,7 @@
     std::set<std::string> build_opts = { ("-DDATA_TYPE=" + get_cl_type_from_data_type(input1->info()->data_type())) };
 
     // Create kernel
-    _kernel = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel(harris_score_kernel_name.str(), build_opts));
+    _kernel = create_kernel(compile_context, harris_score_kernel_name.str(), build_opts);
 
     // Set static kernel arguments
     unsigned int idx = 3 * num_arguments_per_2D_tensor(); //Skip the input and output parameters
diff --git a/src/core/CL/kernels/CLHeightConcatenateLayerKernel.cpp b/src/core/CL/kernels/CLHeightConcatenateLayerKernel.cpp
index a92382d..8d9e1b9 100644
--- a/src/core/CL/kernels/CLHeightConcatenateLayerKernel.cpp
+++ b/src/core/CL/kernels/CLHeightConcatenateLayerKernel.cpp
@@ -91,6 +91,11 @@
 
 void CLHeightConcatenateLayerKernel::configure(const ICLTensor *input, unsigned int height_offset, ICLTensor *output)
 {
+    configure(CLKernelLibrary::get().get_compile_context(), input, height_offset, output);
+}
+
+void CLHeightConcatenateLayerKernel::configure(CLCompileContext &compile_context, const ICLTensor *input, unsigned int height_offset, ICLTensor *output)
+{
     ARM_COMPUTE_ERROR_ON_NULLPTR(input, output);
     ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(input->info(), height_offset, output->info()));
 
@@ -119,7 +124,7 @@
     }
 
     // Create kernel
-    _kernel = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel("concatenate_height", build_opts.options()));
+    _kernel = create_kernel(compile_context, "concatenate_height", build_opts.options());
     // Configure kernel window
 
     ARM_COMPUTE_ERROR_THROW_ON(std::get<0>(win_config));
diff --git a/src/core/CL/kernels/CLHistogramKernel.cpp b/src/core/CL/kernels/CLHistogramKernel.cpp
index adb998d..5c44f6e 100644
--- a/src/core/CL/kernels/CLHistogramKernel.cpp
+++ b/src/core/CL/kernels/CLHistogramKernel.cpp
@@ -53,6 +53,11 @@
 
 void CLHistogramKernel::configure(const ICLImage *input, ICLDistribution1D *output)
 {
+    configure(CLKernelLibrary::get().get_compile_context(), input, output);
+}
+
+void CLHistogramKernel::configure(CLCompileContext &compile_context, const ICLImage *input, ICLDistribution1D *output)
+{
     ARM_COMPUTE_ERROR_ON_TENSOR_NOT_2D(input);
     ARM_COMPUTE_ERROR_ON(nullptr == output);
 
@@ -84,7 +89,7 @@
     // Create kernel
     bool              is_fixed_size = (256 == num_bins) && (1 == window_size) && (0 == offset) && (256 == offrange);
     const std::string kernel_name   = is_fixed_size ? "hist_local_kernel_fixed" : "hist_local_kernel";
-    _kernel                         = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel(kernel_name));
+    _kernel                         = create_kernel(compile_context, kernel_name);
 
     // Set static kernel arguments
     unsigned int idx = num_arguments_per_2D_tensor(); //Skip the input and output parameters
@@ -158,6 +163,11 @@
 
 void CLHistogramBorderKernel::configure(const ICLImage *input, ICLDistribution1D *output)
 {
+    configure(CLKernelLibrary::get().get_compile_context(), input, output);
+}
+
+void CLHistogramBorderKernel::configure(CLCompileContext &compile_context, const ICLImage *input, ICLDistribution1D *output)
+{
     ARM_COMPUTE_ERROR_ON_TENSOR_NOT_2D(input);
     ARM_COMPUTE_ERROR_ON(nullptr == output);
 
@@ -190,7 +200,7 @@
     // Create kernel
     bool              is_fixed_size = (256 == num_bins) && (1 == window_size) && (0 == offset) && (256 == offrange);
     const std::string kernel_name   = is_fixed_size ? "hist_border_kernel_fixed" : "hist_border_kernel";
-    _kernel                         = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel(kernel_name));
+    _kernel                         = create_kernel(compile_context, kernel_name);
 
     // Set static kernel arguments
     unsigned int idx = num_arguments_per_2D_tensor(); //Skip the input and output parameters
diff --git a/src/core/CL/kernels/CLIm2ColKernel.cpp b/src/core/CL/kernels/CLIm2ColKernel.cpp
index 4023c14..b24d250 100644
--- a/src/core/CL/kernels/CLIm2ColKernel.cpp
+++ b/src/core/CL/kernels/CLIm2ColKernel.cpp
@@ -295,6 +295,13 @@
 void CLIm2ColKernel::configure(const ICLTensor *input, ICLTensor *output, const Size2D &kernel_dims, const PadStrideInfo &conv_info, bool has_bias, const Size2D &dilation,
                                unsigned int num_groups)
 {
+    configure(CLKernelLibrary::get().get_compile_context(), input, output, kernel_dims, conv_info, has_bias, dilation, num_groups);
+}
+
+void CLIm2ColKernel::configure(CLCompileContext &compile_context, const ICLTensor *input, ICLTensor *output, const Size2D &kernel_dims, const PadStrideInfo &conv_info, bool has_bias,
+                               const Size2D &dilation,
+                               unsigned int  num_groups)
+{
     ARM_COMPUTE_ERROR_ON_NULLPTR(input, output);
     ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(input->info(), output->info(), kernel_dims, conv_info, has_bias, dilation, num_groups));
 
@@ -311,7 +318,7 @@
     Im2ColConfiguration im2col_config = configure_opencl_kernel(input->info(), kernel_dims, conv_info, has_bias, dilation, num_groups);
 
     // Create kernel
-    _kernel = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel(im2col_config.kernel_name, im2col_config.build_options));
+    _kernel = create_kernel(compile_context, im2col_config.kernel_name, im2col_config.build_options);
 
     _input                             = input;
     _output                            = output;
diff --git a/src/core/CL/kernels/CLInstanceNormalizationLayerKernel.cpp b/src/core/CL/kernels/CLInstanceNormalizationLayerKernel.cpp
index 30684a2..62a0485 100644
--- a/src/core/CL/kernels/CLInstanceNormalizationLayerKernel.cpp
+++ b/src/core/CL/kernels/CLInstanceNormalizationLayerKernel.cpp
@@ -77,6 +77,11 @@
 
 void CLInstanceNormalizationLayerKernel::configure(ICLTensor *input, ICLTensor *output, const InstanceNormalizationLayerKernelInfo &info)
 {
+    configure(CLKernelLibrary::get().get_compile_context(), input, output, info);
+}
+
+void CLInstanceNormalizationLayerKernel::configure(CLCompileContext &compile_context, ICLTensor *input, ICLTensor *output, const InstanceNormalizationLayerKernelInfo &info)
+{
     ARM_COMPUTE_ERROR_ON_NULLPTR(input);
 
     _input  = input;
@@ -100,7 +105,7 @@
     build_opts.add_option_if(_input->info()->data_layout() == DataLayout::NHWC, "-DNHWC");
 
     // Create kernel
-    _kernel = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel("instance_normalization", build_opts.options()));
+    _kernel = create_kernel(compile_context, "instance_normalization", build_opts.options());
 
     // Configure kernel window
     auto win_config = validate_and_configure_window(_input->info(), _output->info());
diff --git a/src/core/CL/kernels/CLIntegralImageKernel.cpp b/src/core/CL/kernels/CLIntegralImageKernel.cpp
index 79aa820..415531d 100644
--- a/src/core/CL/kernels/CLIntegralImageKernel.cpp
+++ b/src/core/CL/kernels/CLIntegralImageKernel.cpp
@@ -39,6 +39,11 @@
 
 void CLIntegralImageHorKernel::configure(const ICLTensor *input, ICLTensor *output)
 {
+    configure(CLKernelLibrary::get().get_compile_context(), input, output);
+}
+
+void CLIntegralImageHorKernel::configure(CLCompileContext &compile_context, const ICLTensor *input, ICLTensor *output)
+{
     ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::U8);
     ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(output, 1, DataType::U32);
 
@@ -47,7 +52,7 @@
 
     // Create kernel
     const std::string kernel_name = std::string("integral_horizontal");
-    _kernel                       = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel(kernel_name));
+    _kernel                       = create_kernel(compile_context, kernel_name);
 
     // Configure kernel window
     const unsigned int num_elems_processed_per_iteration = input->info()->dimension(0);
@@ -85,13 +90,18 @@
 
 void CLIntegralImageVertKernel::configure(ICLTensor *in_out)
 {
+    configure(CLKernelLibrary::get().get_compile_context(), in_out);
+}
+
+void CLIntegralImageVertKernel::configure(CLCompileContext &compile_context, ICLTensor *in_out)
+{
     ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(in_out, 1, DataType::U32);
 
     _in_out = in_out;
 
     // Create kernel
     const std::string kernel_name = std::string("integral_vertical");
-    _kernel                       = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel(kernel_name));
+    _kernel                       = create_kernel(compile_context, kernel_name);
 
     // Configure kernel window
     constexpr unsigned int num_elems_processed_per_iteration_x = 8;
diff --git a/src/core/CL/kernels/CLL2NormalizeLayerKernel.cpp b/src/core/CL/kernels/CLL2NormalizeLayerKernel.cpp
index a0d7be0..1817d15 100644
--- a/src/core/CL/kernels/CLL2NormalizeLayerKernel.cpp
+++ b/src/core/CL/kernels/CLL2NormalizeLayerKernel.cpp
@@ -97,6 +97,11 @@
 
 void CLL2NormalizeLayerKernel::configure(const ICLTensor *input, const ICLTensor *sum, ICLTensor *output, int axis, float epsilon)
 {
+    configure(CLKernelLibrary::get().get_compile_context(), input, sum, output, axis, epsilon);
+}
+
+void CLL2NormalizeLayerKernel::configure(CLCompileContext &compile_context, const ICLTensor *input, const ICLTensor *sum, ICLTensor *output, int axis, float epsilon)
+{
     ARM_COMPUTE_ERROR_ON_NULLPTR(input, sum, output);
     ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(input->info(), sum->info(), output->info(), axis, epsilon));
 
@@ -131,7 +136,7 @@
         default:
             ARM_COMPUTE_ERROR("Axis not supported");
     }
-    _kernel = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel("l2_normalize_" + kernel_name, build_opts));
+    _kernel = create_kernel(compile_context, "l2_normalize_" + kernel_name, build_opts);
 
     // Set epsilon argument
     if(input->info()->data_type() == DataType::F32)
diff --git a/src/core/CL/kernels/CLLKTrackerKernel.cpp b/src/core/CL/kernels/CLLKTrackerKernel.cpp
index 68a210c..3a7c1b5 100644
--- a/src/core/CL/kernels/CLLKTrackerKernel.cpp
+++ b/src/core/CL/kernels/CLLKTrackerKernel.cpp
@@ -1,5 +1,5 @@
 /*
- * Copyright (c) 2017-2019 ARM Limited.
+ * Copyright (c) 2017-2020 ARM Limited.
  *
  * SPDX-License-Identifier: MIT
  *
@@ -41,6 +41,13 @@
 void CLLKTrackerInitKernel::configure(const ICLKeyPointArray *old_points, const ICLKeyPointArray *new_points_estimates,
                                       ICLLKInternalKeypointArray *old_points_internal, ICLLKInternalKeypointArray *new_points_internal,
                                       bool use_initial_estimate, size_t level, size_t num_levels, float pyramid_scale)
+{
+    configure(CLKernelLibrary::get().get_compile_context(), old_points, new_points_estimates, old_points_internal, new_points_internal, use_initial_estimate, level, num_levels, pyramid_scale);
+}
+
+void CLLKTrackerInitKernel::configure(CLCompileContext &compile_context, const ICLKeyPointArray *old_points, const ICLKeyPointArray *new_points_estimates,
+                                      ICLLKInternalKeypointArray *old_points_internal, ICLLKInternalKeypointArray *new_points_internal,
+                                      bool use_initial_estimate, size_t level, size_t num_levels, float pyramid_scale)
 
 {
     ARM_COMPUTE_ERROR_ON(old_points == nullptr);
@@ -55,7 +62,7 @@
     {
         kernel_name += (use_initial_estimate) ? std::string("_max_initial_estimate") : std::string("_max");
     }
-    _kernel = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel(kernel_name));
+    _kernel = create_kernel(compile_context, kernel_name);
 
     // Set static kernel arguments
     unsigned int idx = 0;
@@ -87,13 +94,18 @@
 }
 
 void CLLKTrackerFinalizeKernel::configure(ICLLKInternalKeypointArray *new_points_internal, ICLKeyPointArray *new_points)
+{
+    configure(CLKernelLibrary::get().get_compile_context(), new_points_internal, new_points);
+}
+
+void CLLKTrackerFinalizeKernel::configure(CLCompileContext &compile_context, ICLLKInternalKeypointArray *new_points_internal, ICLKeyPointArray *new_points)
 
 {
     ARM_COMPUTE_ERROR_ON(new_points_internal == nullptr);
     ARM_COMPUTE_ERROR_ON(new_points == nullptr);
 
     // Create kernel
-    _kernel = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel("finalize"));
+    _kernel = create_kernel(compile_context, "finalize");
 
     // Set static kernel arguments
     unsigned int idx = 0;
@@ -124,6 +136,14 @@
                                         ICLLKInternalKeypointArray *old_points_internal, ICLLKInternalKeypointArray *new_points_internal,
                                         ICLCoefficientTableArray *coeff_table, ICLOldValArray *old_ival,
                                         size_t window_dimension, size_t level)
+{
+    configure(CLKernelLibrary::get().get_compile_context(), old_input, old_scharr_gx, old_scharr_gy, old_points_internal, new_points_internal, coeff_table, old_ival, window_dimension, level);
+}
+
+void CLLKTrackerStage0Kernel::configure(CLCompileContext &compile_context, const ICLTensor *old_input, const ICLTensor *old_scharr_gx, const ICLTensor *old_scharr_gy,
+                                        ICLLKInternalKeypointArray *old_points_internal, ICLLKInternalKeypointArray *new_points_internal,
+                                        ICLCoefficientTableArray *coeff_table, ICLOldValArray *old_ival,
+                                        size_t window_dimension, size_t level)
 
 {
     ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(old_input, 1, DataType::U8);
@@ -175,7 +195,7 @@
     };
 
     // Create kernel
-    _kernel = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel("lktracker_stage0"));
+    _kernel = create_kernel(compile_context, "lktracker_stage0");
 
     // Set arguments
     unsigned int idx = 3 * num_arguments_per_2D_tensor();
@@ -212,6 +232,13 @@
 
 void CLLKTrackerStage1Kernel::configure(const ICLTensor *new_input, ICLLKInternalKeypointArray *new_points_internal, ICLCoefficientTableArray *coeff_table, ICLOldValArray *old_ival,
                                         Termination termination, float epsilon, size_t num_iterations, size_t window_dimension, size_t level)
+{
+    configure(CLKernelLibrary::get().get_compile_context(), new_input, new_points_internal, coeff_table, old_ival, termination, epsilon, num_iterations, window_dimension, level);
+}
+
+void CLLKTrackerStage1Kernel::configure(CLCompileContext &compile_context, const ICLTensor *new_input, ICLLKInternalKeypointArray *new_points_internal, ICLCoefficientTableArray *coeff_table,
+                                        ICLOldValArray *old_ival,
+                                        Termination termination, float epsilon, size_t num_iterations, size_t window_dimension, size_t level)
 
 {
     ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(new_input, 1, DataType::U8);
@@ -257,7 +284,7 @@
     const int term_epsilon = (termination == Termination::TERM_CRITERIA_EPSILON || termination == Termination::TERM_CRITERIA_BOTH) ? 1 : 0;
 
     // Create kernel
-    _kernel = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel("lktracker_stage1"));
+    _kernel = create_kernel(compile_context, "lktracker_stage1");
 
     // Set static kernel arguments
     unsigned int idx = num_arguments_per_2D_tensor();
diff --git a/src/core/CL/kernels/CLLocallyConnectedMatrixMultiplyKernel.cpp b/src/core/CL/kernels/CLLocallyConnectedMatrixMultiplyKernel.cpp
index ad2f3a4..fb75058 100644
--- a/src/core/CL/kernels/CLLocallyConnectedMatrixMultiplyKernel.cpp
+++ b/src/core/CL/kernels/CLLocallyConnectedMatrixMultiplyKernel.cpp
@@ -1,5 +1,5 @@
 /*
- * Copyright (c) 2017-2018 ARM Limited.
+ * Copyright (c) 2017-2020 ARM Limited.
  *
  * SPDX-License-Identifier: MIT
  *
@@ -83,6 +83,11 @@
 
 void CLLocallyConnectedMatrixMultiplyKernel::configure(const ICLTensor *input0, const ICLTensor *input1, ICLTensor *output)
 {
+    configure(CLKernelLibrary::get().get_compile_context(), input0, input1, output);
+}
+
+void CLLocallyConnectedMatrixMultiplyKernel::configure(CLCompileContext &compile_context, const ICLTensor *input0, const ICLTensor *input1, ICLTensor *output)
+{
     ARM_COMPUTE_ERROR_ON_NULLPTR(input0, input1, output);
     ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(input0->info(), input1->info(), output->info()));
 
@@ -108,7 +113,7 @@
 
     // Create kernel
     std::string data_type_name = lower_string(string_from_data_type(input0->info()->data_type()));
-    _kernel                    = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel(("gemm_lc_vm_" + data_type_name), build_opts));
+    _kernel                    = create_kernel(compile_context, ("gemm_lc_vm_" + data_type_name), build_opts);
 
     // Configure kernel window
     auto win_config = validate_and_configure_window(input0->info(), input1->info(), output->info());
diff --git a/src/core/CL/kernels/CLMagnitudePhaseKernel.cpp b/src/core/CL/kernels/CLMagnitudePhaseKernel.cpp
index 68f793b..2c28e03 100644
--- a/src/core/CL/kernels/CLMagnitudePhaseKernel.cpp
+++ b/src/core/CL/kernels/CLMagnitudePhaseKernel.cpp
@@ -47,6 +47,12 @@
 void CLMagnitudePhaseKernel::configure(const ICLTensor *gx, const ICLTensor *gy, ICLTensor *magnitude, ICLTensor *phase,
                                        MagnitudeType mag_type, PhaseType phase_type)
 {
+    configure(CLKernelLibrary::get().get_compile_context(), gx, gy, magnitude, phase, mag_type, phase_type);
+}
+
+void CLMagnitudePhaseKernel::configure(CLCompileContext &compile_context, const ICLTensor *gx, const ICLTensor *gy, ICLTensor *magnitude, ICLTensor *phase,
+                                       MagnitudeType mag_type, PhaseType phase_type)
+{
     ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(gx, 1, DataType::S16, DataType::S32);
     ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(gy, 1, DataType::S16, DataType::S32);
     ARM_COMPUTE_ERROR_ON((magnitude == nullptr) && (phase == nullptr));
@@ -118,7 +124,7 @@
 
     // Create kernel
     const std::string kernel_name = std::string("magnitude_phase");
-    _kernel                       = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel(kernel_name, build_opts));
+    _kernel                       = create_kernel(compile_context, kernel_name, build_opts);
 
     // Configure kernel window
     constexpr unsigned int num_elems_processed_per_iteration = 16;
diff --git a/src/core/CL/kernels/CLMeanStdDevKernel.cpp b/src/core/CL/kernels/CLMeanStdDevKernel.cpp
index 7bfd6d6..5a6630d 100644
--- a/src/core/CL/kernels/CLMeanStdDevKernel.cpp
+++ b/src/core/CL/kernels/CLMeanStdDevKernel.cpp
@@ -1,5 +1,5 @@
 /*
- * Copyright (c) 2016-2019 ARM Limited.
+ * Copyright (c) 2016-2020 ARM Limited.
  *
  * SPDX-License-Identifier: MIT
  *
@@ -65,6 +65,11 @@
 
 void CLMeanStdDevKernel::configure(const ICLImage *input, float *mean, cl::Buffer *global_sum, float *stddev, cl::Buffer *global_sum_squared)
 {
+    configure(CLKernelLibrary::get().get_compile_context(), input, mean, global_sum, stddev, global_sum_squared);
+}
+
+void CLMeanStdDevKernel::configure(CLCompileContext &compile_context, const ICLImage *input, float *mean, cl::Buffer *global_sum, float *stddev, cl::Buffer *global_sum_squared)
+{
     ARM_COMPUTE_ERROR_ON_NULLPTR(input, mean, global_sum);
     ARM_COMPUTE_ERROR_ON(stddev && nullptr == global_sum_squared);
     ARM_COMPUTE_ERROR_THROW_ON(CLMeanStdDevKernel::validate(input->info(), mean, global_sum, stddev, global_sum_squared));
@@ -83,7 +88,7 @@
         build_opts.insert("-DSTDDEV");
     }
 
-    _kernel = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel("mean_stddev_accumulate", build_opts));
+    _kernel = create_kernel(compile_context, "mean_stddev_accumulate", build_opts);
 
     // Set fixed arguments
     unsigned int idx = num_arguments_per_2D_tensor(); //Skip the input parameters
diff --git a/src/core/CL/kernels/CLMeanStdDevNormalizationKernel.cpp b/src/core/CL/kernels/CLMeanStdDevNormalizationKernel.cpp
index 72935ce..11ef86e 100644
--- a/src/core/CL/kernels/CLMeanStdDevNormalizationKernel.cpp
+++ b/src/core/CL/kernels/CLMeanStdDevNormalizationKernel.cpp
@@ -85,6 +85,11 @@
 
 void CLMeanStdDevNormalizationKernel::configure(ICLTensor *input, ICLTensor *output, float epsilon)
 {
+    configure(CLKernelLibrary::get().get_compile_context(), input, output, epsilon);
+}
+
+void CLMeanStdDevNormalizationKernel::configure(CLCompileContext &compile_context, ICLTensor *input, ICLTensor *output, float epsilon)
+{
     ARM_COMPUTE_ERROR_ON_NULLPTR(input);
 
     _run_in_place = (output == nullptr) || (output == input);
@@ -105,7 +110,7 @@
     build_opts.add_option_if(_run_in_place, "-DIN_PLACE");
 
     // Create kernel
-    _kernel = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel("mean_stddev_normalization", build_opts.options()));
+    _kernel = create_kernel(compile_context, "mean_stddev_normalization", build_opts.options());
 
     // Configure kernel window
     auto win_config = validate_and_configure_window(input->info(), (_run_in_place) ? nullptr : output->info());
diff --git a/src/core/CL/kernels/CLMedian3x3Kernel.cpp b/src/core/CL/kernels/CLMedian3x3Kernel.cpp
index fca8d9b..cfc9591 100644
--- a/src/core/CL/kernels/CLMedian3x3Kernel.cpp
+++ b/src/core/CL/kernels/CLMedian3x3Kernel.cpp
@@ -39,6 +39,11 @@
 
 void CLMedian3x3Kernel::configure(const ICLTensor *input, ICLTensor *output, bool border_undefined)
 {
+    configure(CLKernelLibrary::get().get_compile_context(), input, output, border_undefined);
+}
+
+void CLMedian3x3Kernel::configure(CLCompileContext &compile_context, const ICLTensor *input, ICLTensor *output, bool border_undefined)
+{
     ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::U8);
     ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(output, 1, DataType::U8);
 
@@ -47,7 +52,7 @@
 
     // Create kernel
     const std::string kernel_name = std::string("non_linear_filter_box3x3");
-    _kernel                       = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel(kernel_name, { "-DMEDIAN" }));
+    _kernel                       = create_kernel(compile_context, kernel_name, { "-DMEDIAN" });
 
     // Configure kernel window
     constexpr unsigned int num_elems_processed_per_iteration = 8;
diff --git a/src/core/CL/kernels/CLMemsetKernel.cpp b/src/core/CL/kernels/CLMemsetKernel.cpp
index b06ae7e..9b37cb8 100644
--- a/src/core/CL/kernels/CLMemsetKernel.cpp
+++ b/src/core/CL/kernels/CLMemsetKernel.cpp
@@ -44,6 +44,13 @@
                                const PixelValue &constant_value,
                                Window           *window)
 {
+    configure(CLKernelLibrary::get().get_compile_context(), tensor, constant_value, window);
+}
+
+void CLMemsetKernel::configure(CLCompileContext &compile_context, ICLTensor *tensor,
+                               const PixelValue &constant_value,
+                               Window           *window)
+{
     ARM_COMPUTE_ERROR_ON_NULLPTR(tensor);
     ARM_COMPUTE_ERROR_THROW_ON(validate(tensor->info(), constant_value, window));
 
@@ -77,7 +84,7 @@
     build_opts.add_option("-DCONSTANT_VALUE=" + string_from_pixel_value(constant_value, data_type));
     build_opts.add_option_if(multi_access_x, "-DVEC_SIZE=" + support::cpp11::to_string(vec_size_x));
     build_opts.add_option_if(multi_access_x && remainder_x, "-DLAST_ACCESSED_X=" + support::cpp11::to_string(std::max<int>(output_width_x - vec_size_x, 0)));
-    _kernel = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel("memset", build_opts.options()));
+    _kernel = create_kernel(compile_context, "memset", build_opts.options());
 }
 
 Status CLMemsetKernel::validate(const ITensorInfo *tensor, const PixelValue &constant_value, Window *window)
diff --git a/src/core/CL/kernels/CLMinMaxLayerKernel.cpp b/src/core/CL/kernels/CLMinMaxLayerKernel.cpp
index 622270a..c89bbcb 100644
--- a/src/core/CL/kernels/CLMinMaxLayerKernel.cpp
+++ b/src/core/CL/kernels/CLMinMaxLayerKernel.cpp
@@ -88,6 +88,11 @@
 
 void CLMinMaxLayerKernel::configure(const ICLTensor *input, ICLTensor *output)
 {
+    configure(CLKernelLibrary::get().get_compile_context(), input, output);
+}
+
+void CLMinMaxLayerKernel::configure(CLCompileContext &compile_context, const ICLTensor *input, ICLTensor *output)
+{
     ARM_COMPUTE_ERROR_ON_NULLPTR(input, output);
     ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(input->info(), output->info()));
 
@@ -100,7 +105,7 @@
     build_opts.emplace("-DDEPTH=" + support::cpp11::to_string(input->info()->dimension(2)));
 
     // Create kernel
-    _kernel = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel("minmax_layer", build_opts));
+    _kernel = create_kernel(compile_context, "minmax_layer", build_opts);
 
     auto win_config = validate_and_configure_window(input->info(), output->info());
 
diff --git a/src/core/CL/kernels/CLMinMaxLocationKernel.cpp b/src/core/CL/kernels/CLMinMaxLocationKernel.cpp
index 3cead37..77c945b 100644
--- a/src/core/CL/kernels/CLMinMaxLocationKernel.cpp
+++ b/src/core/CL/kernels/CLMinMaxLocationKernel.cpp
@@ -62,6 +62,11 @@
 
 void CLMinMaxKernel::configure(const ICLImage *input, cl::Buffer *min_max)
 {
+    configure(CLKernelLibrary::get().get_compile_context(), input, min_max);
+}
+
+void CLMinMaxKernel::configure(CLCompileContext &compile_context, const ICLImage *input, cl::Buffer *min_max)
+{
     ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::U8, DataType::S16, DataType::F32);
     ARM_COMPUTE_ERROR_ON_TENSOR_NOT_2D(input);
     ARM_COMPUTE_ERROR_ON(min_max == nullptr);
@@ -109,7 +114,7 @@
     }
 
     // Create kernel
-    _kernel = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel("minmax", build_opts));
+    _kernel = create_kernel(compile_context, "minmax", build_opts);
 
     // Set fixed arguments
     unsigned int idx = num_arguments_per_2D_tensor(); //Skip the input and output parameters
@@ -169,6 +174,12 @@
 
 void CLMinMaxLocationKernel::configure(const ICLImage *input, cl::Buffer *min_max, cl::Buffer *min_max_count, ICLCoordinates2DArray *min_loc, ICLCoordinates2DArray *max_loc)
 {
+    configure(CLKernelLibrary::get().get_compile_context(), input, min_max, min_max_count, min_loc, max_loc);
+}
+
+void CLMinMaxLocationKernel::configure(CLCompileContext &compile_context, const ICLImage *input, cl::Buffer *min_max, cl::Buffer *min_max_count, ICLCoordinates2DArray *min_loc,
+                                       ICLCoordinates2DArray *max_loc)
+{
     ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::U8, DataType::S16, DataType::F32);
     ARM_COMPUTE_ERROR_ON_TENSOR_NOT_2D(input);
     ARM_COMPUTE_ERROR_ON(min_max == nullptr);
@@ -189,7 +200,7 @@
     }
 
     // Create kernel
-    _kernel = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel("minmaxloc", build_opts));
+    _kernel = create_kernel(compile_context, "minmaxloc", build_opts);
 
     // Set static arguments
     unsigned int idx = num_arguments_per_2D_tensor(); //Skip the input and output parameters
diff --git a/src/core/CL/kernels/CLNonLinearFilterKernel.cpp b/src/core/CL/kernels/CLNonLinearFilterKernel.cpp
index 5e41974..01b8733 100644
--- a/src/core/CL/kernels/CLNonLinearFilterKernel.cpp
+++ b/src/core/CL/kernels/CLNonLinearFilterKernel.cpp
@@ -1,5 +1,5 @@
 /*
- * Copyright (c) 2017-2018 ARM Limited.
+ * Copyright (c) 2017-2020 ARM Limited.
  *
  * SPDX-License-Identifier: MIT
  *
@@ -57,6 +57,13 @@
                                         unsigned int mask_size, MatrixPattern pattern, const uint8_t *mask,
                                         bool border_undefined)
 {
+    configure(CLKernelLibrary::get().get_compile_context(), input, output, function, mask_size, pattern, mask, border_undefined);
+}
+
+void CLNonLinearFilterKernel::configure(CLCompileContext &compile_context, const ICLTensor *input, ICLTensor *output, NonLinearFilterFunction function,
+                                        unsigned int mask_size, MatrixPattern pattern, const uint8_t *mask,
+                                        bool border_undefined)
+{
     ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::U8);
     ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(output, 1, DataType::U8);
     ARM_COMPUTE_ERROR_ON(mask_size != 3 && mask_size != 5);
@@ -78,7 +85,7 @@
     ss << "non_linear_filter_" << pattern_name << mask_size << "x" << mask_size;
 
     // Create kernel
-    _kernel = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel(ss.str(), build_opts));
+    _kernel = create_kernel(compile_context, ss.str(), build_opts);
 
     // Configure kernel window
     constexpr unsigned int num_elems_processed_per_iteration = 8;
diff --git a/src/core/CL/kernels/CLNonMaximaSuppression3x3Kernel.cpp b/src/core/CL/kernels/CLNonMaximaSuppression3x3Kernel.cpp
index 4e41f0d..dd6aa1e 100644
--- a/src/core/CL/kernels/CLNonMaximaSuppression3x3Kernel.cpp
+++ b/src/core/CL/kernels/CLNonMaximaSuppression3x3Kernel.cpp
@@ -1,5 +1,5 @@
 /*
- * Copyright (c) 2016-2018 ARM Limited.
+ * Copyright (c) 2016-2020 ARM Limited.
  *
  * SPDX-License-Identifier: MIT
  *
@@ -43,6 +43,11 @@
 
 void CLNonMaximaSuppression3x3Kernel::configure(const ICLTensor *input, ICLTensor *output, bool border_undefined)
 {
+    configure(CLKernelLibrary::get().get_compile_context(), input, output, border_undefined);
+}
+
+void CLNonMaximaSuppression3x3Kernel::configure(CLCompileContext &compile_context, const ICLTensor *input, ICLTensor *output, bool border_undefined)
+{
     ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::U8, DataType::F32);
     ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(output, 1, DataType::U8, DataType::F32);
 
@@ -51,7 +56,7 @@
 
     // Create kernel
     std::set<std::string> build_opts = { ("-DDATA_TYPE=" + get_cl_type_from_data_type(input->info()->data_type())) };
-    _kernel                          = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel("non_max_suppression", build_opts));
+    _kernel                          = create_kernel(compile_context, "non_max_suppression", build_opts);
 
     // Configure kernel window
     constexpr unsigned int num_elems_processed_per_iteration = 8;
diff --git a/src/core/CL/kernels/CLNormalizationLayerKernel.cpp b/src/core/CL/kernels/CLNormalizationLayerKernel.cpp
index 024d1de..6284a6a 100644
--- a/src/core/CL/kernels/CLNormalizationLayerKernel.cpp
+++ b/src/core/CL/kernels/CLNormalizationLayerKernel.cpp
@@ -107,6 +107,11 @@
 
 void CLNormalizationLayerKernel::configure(const ICLTensor *input, ICLTensor *output, NormalizationLayerInfo norm_info)
 {
+    configure(CLKernelLibrary::get().get_compile_context(), input, output, norm_info);
+}
+
+void CLNormalizationLayerKernel::configure(CLCompileContext &compile_context, const ICLTensor *input, ICLTensor *output, NormalizationLayerInfo norm_info)
+{
     ARM_COMPUTE_ERROR_ON_NULLPTR(input, output);
 
     // Output tensor auto initialization if not yet initialized
@@ -156,7 +161,7 @@
             kernel_name = "normalization_layer_in_map_nchw";
         }
     }
-    _kernel = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel(kernel_name, build_opts.options()));
+    _kernel = create_kernel(compile_context, kernel_name, build_opts.options());
 
     // Configure kernel window
     auto win_config = validate_and_configure_window(input->info(), output->info(), norm_info);
diff --git a/src/core/CL/kernels/CLNormalizePlanarYUVLayerKernel.cpp b/src/core/CL/kernels/CLNormalizePlanarYUVLayerKernel.cpp
index c713e1f..d46581e 100644
--- a/src/core/CL/kernels/CLNormalizePlanarYUVLayerKernel.cpp
+++ b/src/core/CL/kernels/CLNormalizePlanarYUVLayerKernel.cpp
@@ -97,6 +97,11 @@
 
 void CLNormalizePlanarYUVLayerKernel::configure(const ICLTensor *input, ICLTensor *output, const ICLTensor *mean, const ICLTensor *std)
 {
+    configure(CLKernelLibrary::get().get_compile_context(), input, output, mean, std);
+}
+
+void CLNormalizePlanarYUVLayerKernel::configure(CLCompileContext &compile_context, const ICLTensor *input, ICLTensor *output, const ICLTensor *mean, const ICLTensor *std)
+{
     // Perform validation step
     ARM_COMPUTE_ERROR_ON_NULLPTR(input, output, mean, std);
     ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(input->info(), output->info(), mean->info(), std->info()));
@@ -127,7 +132,7 @@
 
     // Create kernel
     kernel_name += lower_string(string_from_data_layout(input->info()->data_layout()));
-    _kernel = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel(kernel_name, build_opts.options()));
+    _kernel = create_kernel(compile_context, kernel_name, build_opts.options());
 
     // Configure kernel window
     auto win_config = validate_and_configure_window(input->info(), output->info(), mean->info(), std->info());
diff --git a/src/core/CL/kernels/CLPadLayerKernel.cpp b/src/core/CL/kernels/CLPadLayerKernel.cpp
index 3eeef55..764e2a4 100644
--- a/src/core/CL/kernels/CLPadLayerKernel.cpp
+++ b/src/core/CL/kernels/CLPadLayerKernel.cpp
@@ -98,6 +98,11 @@
 
 void CLPadLayerKernel::configure(const ICLTensor *input, ICLTensor *output, const PaddingList &padding, PixelValue constant_value, PaddingMode mode)
 {
+    configure(CLKernelLibrary::get().get_compile_context(), input, output, padding, constant_value, mode);
+}
+
+void CLPadLayerKernel::configure(CLCompileContext &compile_context, const ICLTensor *input, ICLTensor *output, const PaddingList &padding, PixelValue constant_value, PaddingMode mode)
+{
     // Perform validation step
     ARM_COMPUTE_ERROR_ON_NULLPTR(input, output);
     ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(input->info(), output->info(), padding, constant_value, mode));
@@ -189,7 +194,7 @@
     }
 
     // Create kernel
-    _kernel = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel(kernel_name, build_opts.options()));
+    _kernel = create_kernel(compile_context, kernel_name, build_opts.options());
 }
 
 Status CLPadLayerKernel::validate(const ITensorInfo *input, const ITensorInfo *output, const PaddingList &padding, PixelValue constant_value, PaddingMode mode)
diff --git a/src/core/CL/kernels/CLPermuteKernel.cpp b/src/core/CL/kernels/CLPermuteKernel.cpp
index 9a4d72d..3f1f870 100644
--- a/src/core/CL/kernels/CLPermuteKernel.cpp
+++ b/src/core/CL/kernels/CLPermuteKernel.cpp
@@ -77,6 +77,11 @@
 
 void CLPermuteKernel::configure(const ICLTensor *input, ICLTensor *output, const PermutationVector &perm)
 {
+    configure(CLKernelLibrary::get().get_compile_context(), input, output, perm);
+}
+
+void CLPermuteKernel::configure(CLCompileContext &compile_context, const ICLTensor *input, ICLTensor *output, const PermutationVector &perm)
+{
     ARM_COMPUTE_ERROR_ON_NULLPTR(input, output);
     ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(input->info(), output->info(), perm));
 
@@ -98,7 +103,7 @@
     build_opts.add_option("-DP3=" + support::cpp11::to_string((_perm.num_dimensions() >= 3) ? perm[2] : 2));
     build_opts.add_option("-DP4=" + support::cpp11::to_string((_perm.num_dimensions() >= 4) ? perm[3] : 3));
 
-    _kernel = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel("permute", build_opts.options()));
+    _kernel = create_kernel(compile_context, "permute", build_opts.options());
 
     // Configure  kernel window
     Window win = calculate_max_window(*input->info(), Steps());
diff --git a/src/core/CL/kernels/CLPixelWiseMultiplicationKernel.cpp b/src/core/CL/kernels/CLPixelWiseMultiplicationKernel.cpp
index 2df3ff4..49f5e04 100644
--- a/src/core/CL/kernels/CLPixelWiseMultiplicationKernel.cpp
+++ b/src/core/CL/kernels/CLPixelWiseMultiplicationKernel.cpp
@@ -145,6 +145,12 @@
 void CLPixelWiseMultiplicationKernel::configure(const ICLTensor *input1, const ICLTensor *input2, ICLTensor *output, float scale,
                                                 ConvertPolicy overflow_policy, RoundingPolicy rounding_policy, const ActivationLayerInfo &act_info)
 {
+    configure(CLKernelLibrary::get().get_compile_context(), input1, input2, output, scale, overflow_policy, rounding_policy, act_info);
+}
+
+void CLPixelWiseMultiplicationKernel::configure(CLCompileContext &compile_context, const ICLTensor *input1, const ICLTensor *input2, ICLTensor *output, float scale,
+                                                ConvertPolicy overflow_policy, RoundingPolicy rounding_policy, const ActivationLayerInfo &act_info)
+{
     ARM_COMPUTE_ERROR_ON_NULLPTR(input1, input2, output);
     ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(input1->info(), input2->info(), output->info(),
                                                   scale, overflow_policy, rounding_policy, act_info));
@@ -233,7 +239,7 @@
     }
 
     // Create kernel
-    _kernel = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel(kernel_name, build_opts.options()));
+    _kernel = create_kernel(compile_context, kernel_name, build_opts.options());
 
     // Set scale argument
     unsigned int idx = 3 * num_arguments_per_3D_tensor(); // Skip the inputs and output parameters
@@ -370,6 +376,11 @@
 
 void CLComplexPixelWiseMultiplicationKernel::configure(const ICLTensor *input1, const ICLTensor *input2, ICLTensor *output, const ActivationLayerInfo &act_info)
 {
+    configure(CLKernelLibrary::get().get_compile_context(), input1, input2, output, act_info);
+}
+
+void CLComplexPixelWiseMultiplicationKernel::configure(CLCompileContext &compile_context, const ICLTensor *input1, const ICLTensor *input2, ICLTensor *output, const ActivationLayerInfo &act_info)
+{
     ARM_COMPUTE_ERROR_ON_NULLPTR(input1, input2, output);
     ARM_COMPUTE_ERROR_THROW_ON(validate_arguments_complex(input1->info(), input2->info(), output->info(), act_info));
 
@@ -390,7 +401,7 @@
     }
 
     // Create kernel
-    _kernel = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel("pixelwise_mul_complex", build_opts.options()));
+    _kernel = create_kernel(compile_context, "pixelwise_mul_complex", build_opts.options());
 
     ICLKernel::configure_internal(win_config.second);
 }
diff --git a/src/core/CL/kernels/CLPoolingLayerKernel.cpp b/src/core/CL/kernels/CLPoolingLayerKernel.cpp
index dbbca47..43b8f85 100644
--- a/src/core/CL/kernels/CLPoolingLayerKernel.cpp
+++ b/src/core/CL/kernels/CLPoolingLayerKernel.cpp
@@ -178,6 +178,11 @@
 
 void CLPoolingLayerKernel::configure(const ICLTensor *input, ICLTensor *output, const PoolingLayerInfo &pool_info, ICLTensor *indices)
 {
+    configure(CLKernelLibrary::get().get_compile_context(), input, output, pool_info, indices);
+}
+
+void CLPoolingLayerKernel::configure(CLCompileContext &compile_context, const ICLTensor *input, ICLTensor *output, const PoolingLayerInfo &pool_info, ICLTensor *indices)
+{
     ARM_COMPUTE_ERROR_ON_NULLPTR(input, output);
 
     // Set instance variables
@@ -275,12 +280,12 @@
 
                 std::string kernel_name = ((is_pool3x3_stride_le3) ? "pooling_layer_optimized_" : "pooling_layer_")
                                           + support::cpp11::to_string(pool_size_x);
-                _kernel = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel(kernel_name, build_opts.options()));
+                _kernel = create_kernel(compile_context, kernel_name, build_opts.options());
             }
             else // Run general case
             {
                 std::string kernel_name = is_data_type_quantized_asymmetric(data_type) ? "pooling_layer_MxN_quantized_nchw" : "pooling_layer_MxN_nchw";
-                _kernel                 = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel(kernel_name, build_opts.options()));
+                _kernel                 = create_kernel(compile_context, kernel_name, build_opts.options());
             }
             break;
         }
@@ -292,7 +297,7 @@
             build_opts.add_option_if(output->info()->tensor_shape().total_size_upper(3) > 1,
                                      "-DDST_DEPTH=" + support::cpp11::to_string(output->info()->dimension(idx_height)));
             std::string kernel_name = is_data_type_quantized_asymmetric(data_type) ? "pooling_layer_MxN_quantized_nhwc" : "pooling_layer_MxN_nhwc";
-            _kernel                 = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel(kernel_name, build_opts.options()));
+            _kernel                 = create_kernel(compile_context, kernel_name, build_opts.options());
             break;
         }
         default:
diff --git a/src/core/CL/kernels/CLPriorBoxLayerKernel.cpp b/src/core/CL/kernels/CLPriorBoxLayerKernel.cpp
index ed70f4d..9f930c5 100644
--- a/src/core/CL/kernels/CLPriorBoxLayerKernel.cpp
+++ b/src/core/CL/kernels/CLPriorBoxLayerKernel.cpp
@@ -102,6 +102,12 @@
 
 void CLPriorBoxLayerKernel::configure(const ICLTensor *input1, const ICLTensor *input2, ICLTensor *output, const PriorBoxLayerInfo &info, cl::Buffer *min, cl::Buffer *max, cl::Buffer *aspect_ratios)
 {
+    configure(CLKernelLibrary::get().get_compile_context(), input1, input2, output, info, min, max, aspect_ratios);
+}
+
+void CLPriorBoxLayerKernel::configure(CLCompileContext &compile_context, const ICLTensor *input1, const ICLTensor *input2, ICLTensor *output, const PriorBoxLayerInfo &info, cl::Buffer *min,
+                                      cl::Buffer *max, cl::Buffer *aspect_ratios)
+{
     ARM_COMPUTE_ERROR_ON_NULLPTR(input1, input2, output);
 
     _input1        = input1;
@@ -170,7 +176,7 @@
     }
 
     unsigned int idx = num_arguments_per_2D_tensor();
-    _kernel          = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel("prior_box_layer_nchw", build_opts.options()));
+    _kernel          = create_kernel(compile_context, "prior_box_layer_nchw", build_opts.options());
 
     _kernel.setArg(idx++, *_min);
     _kernel.setArg(idx++, *_max);
diff --git a/src/core/CL/kernels/CLQuantizationLayerKernel.cpp b/src/core/CL/kernels/CLQuantizationLayerKernel.cpp
index 2ec2bd1..e017946 100644
--- a/src/core/CL/kernels/CLQuantizationLayerKernel.cpp
+++ b/src/core/CL/kernels/CLQuantizationLayerKernel.cpp
@@ -81,6 +81,11 @@
 
 void CLQuantizationLayerKernel::configure(const ICLTensor *input, ICLTensor *output)
 {
+    configure(CLKernelLibrary::get().get_compile_context(), input, output);
+}
+
+void CLQuantizationLayerKernel::configure(CLCompileContext &compile_context, const ICLTensor *input, ICLTensor *output)
+{
     ARM_COMPUTE_ERROR_ON_NULLPTR(input, output);
     ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(input->info(), output->info()));
 
@@ -154,7 +159,7 @@
     build_opts.add_option("-DMIN_QUANT_VAL=" + support::cpp11::to_string(min_max_quant_values.first));
     build_opts.add_option("-DMAX_QUANT_VAL=" + support::cpp11::to_string(min_max_quant_values.second));
 
-    _kernel = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel("quantization_layer", build_opts.options()));
+    _kernel = create_kernel(compile_context, "quantization_layer", build_opts.options());
 }
 
 Status CLQuantizationLayerKernel::validate(const ITensorInfo *input, const ITensorInfo *output)
diff --git a/src/core/CL/kernels/CLROIAlignLayerKernel.cpp b/src/core/CL/kernels/CLROIAlignLayerKernel.cpp
index 41ed8ed..cc1af52 100644
--- a/src/core/CL/kernels/CLROIAlignLayerKernel.cpp
+++ b/src/core/CL/kernels/CLROIAlignLayerKernel.cpp
@@ -105,6 +105,11 @@
 
 void CLROIAlignLayerKernel::configure(const ICLTensor *input, const ICLTensor *rois, ICLTensor *output, const ROIPoolingLayerInfo &pool_info)
 {
+    configure(CLKernelLibrary::get().get_compile_context(), input, rois, output, pool_info);
+}
+
+void CLROIAlignLayerKernel::configure(CLCompileContext &compile_context, const ICLTensor *input, const ICLTensor *rois, ICLTensor *output, const ROIPoolingLayerInfo &pool_info)
+{
     ARM_COMPUTE_ERROR_ON_NULLPTR(input, output, rois);
     ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(input->info(), rois->info(), output->info(), pool_info));
 
@@ -149,7 +154,7 @@
 
     // Create kernel
     const std::string kernel_name = (is_qasymm) ? "roi_align_layer_quantized" : "roi_align_layer";
-    _kernel                       = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel(kernel_name, build_opts.options()));
+    _kernel                       = create_kernel(compile_context, kernel_name, build_opts.options());
 
     ICLKernel::configure_internal(win_config.second);
 }
diff --git a/src/core/CL/kernels/CLROIPoolingLayerKernel.cpp b/src/core/CL/kernels/CLROIPoolingLayerKernel.cpp
index dad33b1..5f64215 100644
--- a/src/core/CL/kernels/CLROIPoolingLayerKernel.cpp
+++ b/src/core/CL/kernels/CLROIPoolingLayerKernel.cpp
@@ -73,6 +73,11 @@
 
 void CLROIPoolingLayerKernel::configure(const ICLTensor *input, const ICLTensor *rois, ICLTensor *output, const ROIPoolingLayerInfo &pool_info)
 {
+    configure(CLKernelLibrary::get().get_compile_context(), input, rois, output, pool_info);
+}
+
+void CLROIPoolingLayerKernel::configure(CLCompileContext &compile_context, const ICLTensor *input, const ICLTensor *rois, ICLTensor *output, const ROIPoolingLayerInfo &pool_info)
+{
     ARM_COMPUTE_ERROR_ON_NULLPTR(input, rois, output);
 
     //Validate arguments
@@ -115,7 +120,7 @@
 
     // Create kernel
     std::string kernel_name = "roi_pooling_layer";
-    _kernel                 = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel(kernel_name, build_opts));
+    _kernel                 = create_kernel(compile_context, kernel_name, build_opts);
 
     // Set static kernel arguments
     unsigned int idx = 2 * num_arguments_per_3D_tensor() + num_arguments_per_1D_array();
diff --git a/src/core/CL/kernels/CLRangeKernel.cpp b/src/core/CL/kernels/CLRangeKernel.cpp
index 4024de7..97b5f01 100644
--- a/src/core/CL/kernels/CLRangeKernel.cpp
+++ b/src/core/CL/kernels/CLRangeKernel.cpp
@@ -93,6 +93,11 @@
 
 void CLRangeKernel::configure(ICLTensor *output, const float start, const float end, const float step)
 {
+    configure(CLKernelLibrary::get().get_compile_context(), output, start, end, step);
+}
+
+void CLRangeKernel::configure(CLCompileContext &compile_context, ICLTensor *output, const float start, const float end, const float step)
+{
     ARM_COMPUTE_ERROR_ON_NULLPTR(output);
 
     ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(*(output->info()), start, end, step));
@@ -123,7 +128,7 @@
         kernel_name += "_quantized";
     }
     // Create kernel
-    _kernel = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel(kernel_name, build_opts.options()));
+    _kernel = create_kernel(compile_context, kernel_name, build_opts.options());
     ICLKernel::configure_internal(win_config.second);
 
     // Set config_id for enabling LWS tuning
diff --git a/src/core/CL/kernels/CLReductionOperationKernel.cpp b/src/core/CL/kernels/CLReductionOperationKernel.cpp
index 7563f02..5c76016 100644
--- a/src/core/CL/kernels/CLReductionOperationKernel.cpp
+++ b/src/core/CL/kernels/CLReductionOperationKernel.cpp
@@ -129,6 +129,11 @@
 
 void CLReductionOperationKernel::configure(const ICLTensor *input, ICLTensor *output, unsigned int axis, ReductionOperation op, unsigned int width)
 {
+    configure(CLKernelLibrary::get().get_compile_context(), input, output, axis, op, width);
+}
+
+void CLReductionOperationKernel::configure(CLCompileContext &compile_context, const ICLTensor *input, ICLTensor *output, unsigned int axis, ReductionOperation op, unsigned int width)
+{
     ARM_COMPUTE_ERROR_ON_NULLPTR(input, output);
 
     ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(input->info(), output->info(), axis, op, width));
@@ -227,7 +232,7 @@
         default:
             ARM_COMPUTE_ERROR("Not supported");
     }
-    _kernel = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel("reduction_operation_" + kernel_axis_name, build_opts.options()));
+    _kernel = create_kernel(compile_context, "reduction_operation_" + kernel_axis_name, build_opts.options());
 
     // Configure kernel window
     auto win_config = validate_and_configure_window(_input->info(), _output->info(), axis, op);
diff --git a/src/core/CL/kernels/CLRemapKernel.cpp b/src/core/CL/kernels/CLRemapKernel.cpp
index 12161fc..fb425b5 100644
--- a/src/core/CL/kernels/CLRemapKernel.cpp
+++ b/src/core/CL/kernels/CLRemapKernel.cpp
@@ -1,5 +1,5 @@
 /*
- * Copyright (c) 2017-2019 ARM Limited.
+ * Copyright (c) 2017-2020 ARM Limited.
  *
  * SPDX-License-Identifier: MIT
  *
@@ -49,6 +49,12 @@
 
 void CLRemapKernel::configure(const ICLTensor *input, const ICLTensor *map_x, const ICLTensor *map_y, ICLTensor *output, InterpolationPolicy policy, bool border_undefined)
 {
+    configure(CLKernelLibrary::get().get_compile_context(), input, map_x, map_y, output, policy, border_undefined);
+}
+
+void CLRemapKernel::configure(CLCompileContext &compile_context, const ICLTensor *input, const ICLTensor *map_x, const ICLTensor *map_y, ICLTensor *output, InterpolationPolicy policy,
+                              bool border_undefined)
+{
     ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::U8);
     ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(output, 1, DataType::U8);
     ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(map_x, 1, DataType::F32);
@@ -66,7 +72,7 @@
     std::string           interpolation_name = string_from_interpolation_policy(policy);
     std::transform(interpolation_name.begin(), interpolation_name.end(), interpolation_name.begin(), ::tolower);
     std::string kernel_name = "remap_" + interpolation_name;
-    _kernel                 = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel(kernel_name, build_opts));
+    _kernel                 = create_kernel(compile_context, kernel_name, build_opts);
 
     // Configure window
     constexpr unsigned int num_elems_processed_per_iteration = 4;
diff --git a/src/core/CL/kernels/CLReorgLayerKernel.cpp b/src/core/CL/kernels/CLReorgLayerKernel.cpp
index 4aa50c1..e36bcbb 100644
--- a/src/core/CL/kernels/CLReorgLayerKernel.cpp
+++ b/src/core/CL/kernels/CLReorgLayerKernel.cpp
@@ -72,6 +72,11 @@
 
 void CLReorgLayerKernel::configure(const ICLTensor *input, ICLTensor *output, int32_t stride)
 {
+    configure(CLKernelLibrary::get().get_compile_context(), input, output, stride);
+}
+
+void CLReorgLayerKernel::configure(CLCompileContext &compile_context, const ICLTensor *input, ICLTensor *output, int32_t stride)
+{
     ARM_COMPUTE_ERROR_ON_NULLPTR(input, output);
     ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(input->info(), output->info(), stride));
 
@@ -86,7 +91,7 @@
     build_opts.add_option("-DDATA_TYPE=" + get_cl_type_from_data_type(input->info()->data_type()));
     build_opts.add_option("-DSRC_DEPTH=" + support::cpp11::to_string(input->info()->dimension(idx_channel)));
     build_opts.add_option("-DSTRIDE=" + support::cpp11::to_string(stride));
-    _kernel = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel(kernel_name, build_opts.options()));
+    _kernel = create_kernel(compile_context, kernel_name, build_opts.options());
 
     // Configure window
     // auto inizialize the output tensor if not yet initialized
diff --git a/src/core/CL/kernels/CLReshapeLayerKernel.cpp b/src/core/CL/kernels/CLReshapeLayerKernel.cpp
index a6053d9..33a1cea 100644
--- a/src/core/CL/kernels/CLReshapeLayerKernel.cpp
+++ b/src/core/CL/kernels/CLReshapeLayerKernel.cpp
@@ -1,5 +1,5 @@
 /*
- * Copyright (c) 2017-2019 ARM Limited.
+ * Copyright (c) 2017-2020 ARM Limited.
  *
  * SPDX-License-Identifier: MIT
  *
@@ -64,6 +64,11 @@
 
 void CLReshapeLayerKernel::configure(const ICLTensor *input, ICLTensor *output)
 {
+    configure(CLKernelLibrary::get().get_compile_context(), input, output);
+}
+
+void CLReshapeLayerKernel::configure(CLCompileContext &compile_context, const ICLTensor *input, ICLTensor *output)
+{
     ARM_COMPUTE_ERROR_ON_NULLPTR(input, output);
     ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(input->info(), output->info()));
 
@@ -72,7 +77,7 @@
 
     // Create kernel
     std::set<std::string> build_opts = { "-DDATA_TYPE=" + get_cl_unsigned_type_from_element_size(input->info()->element_size()) };
-    _kernel                          = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel("reshape_layer", build_opts));
+    _kernel                          = create_kernel(compile_context, "reshape_layer", build_opts);
 
     // Add static arguments
     const cl_int2 input_shape =
diff --git a/src/core/CL/kernels/CLReverseKernel.cpp b/src/core/CL/kernels/CLReverseKernel.cpp
index 83708e2..d88a78c 100644
--- a/src/core/CL/kernels/CLReverseKernel.cpp
+++ b/src/core/CL/kernels/CLReverseKernel.cpp
@@ -65,6 +65,11 @@
 
 void CLReverseKernel::configure(const ICLTensor *input, ICLTensor *output, const ICLTensor *axis)
 {
+    configure(CLKernelLibrary::get().get_compile_context(), input, output, axis);
+}
+
+void CLReverseKernel::configure(CLCompileContext &compile_context, const ICLTensor *input, ICLTensor *output, const ICLTensor *axis)
+{
     ARM_COMPUTE_ERROR_ON_NULLPTR(input, output, axis);
 
     _input  = input;
@@ -82,7 +87,7 @@
     build_opts.add_option("-DDATA_TYPE=" + get_cl_unsigned_type_from_element_size(input->info()->element_size()));
 
     // Create kernel
-    _kernel = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel("reverse", build_opts.options()));
+    _kernel = create_kernel(compile_context, "reverse", build_opts.options());
 
     // Set static kernel arguments
     unsigned int idx = 2 * num_arguments_per_4D_tensor() + num_arguments_per_1D_tensor();
diff --git a/src/core/CL/kernels/CLScaleKernel.cpp b/src/core/CL/kernels/CLScaleKernel.cpp
index 244afb5..33c7ad7 100644
--- a/src/core/CL/kernels/CLScaleKernel.cpp
+++ b/src/core/CL/kernels/CLScaleKernel.cpp
@@ -182,6 +182,12 @@
 
 void CLScaleKernel::configure(const ICLTensor *input, ICLTensor *output, InterpolationPolicy policy, BorderMode border_mode, SamplingPolicy sampling_policy, bool align_corners)
 {
+    configure(CLKernelLibrary::get().get_compile_context(), input, output, policy, border_mode, sampling_policy, align_corners);
+}
+
+void CLScaleKernel::configure(CLCompileContext &compile_context, const ICLTensor *input, ICLTensor *output, InterpolationPolicy policy, BorderMode border_mode, SamplingPolicy sampling_policy,
+                              bool align_corners)
+{
     _align_corners = policy == InterpolationPolicy::BILINEAR
                      && sampling_policy == SamplingPolicy::TOP_LEFT
                      && align_corners;
@@ -236,7 +242,7 @@
     std::string kernel_name = "scale_" + interpolation_name;
     kernel_name += call_quantized_kernel ? "_quantized_" : "_";
     kernel_name += lower_string(string_from_data_layout(_data_layout));
-    _kernel = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel(kernel_name, build_opts.options()));
+    _kernel = create_kernel(compile_context, kernel_name, build_opts.options());
 
     unsigned int idx = is_nhwc ? 2 * num_arguments_per_4D_tensor() : 2 * num_arguments_per_2D_tensor(); //Skip the input and output parameters
 
diff --git a/src/core/CL/kernels/CLScharr3x3Kernel.cpp b/src/core/CL/kernels/CLScharr3x3Kernel.cpp
index 94b0d38..9f5bdb3 100644
--- a/src/core/CL/kernels/CLScharr3x3Kernel.cpp
+++ b/src/core/CL/kernels/CLScharr3x3Kernel.cpp
@@ -1,5 +1,5 @@
 /*
- * Copyright (c) 2016-2019 ARM Limited.
+ * Copyright (c) 2016-2020 ARM Limited.
  *
  * SPDX-License-Identifier: MIT
  *
@@ -49,6 +49,11 @@
 
 void CLScharr3x3Kernel::configure(const ICLTensor *input, ICLTensor *output_x, ICLTensor *output_y, bool border_undefined)
 {
+    configure(CLKernelLibrary::get().get_compile_context(), input, output_x, output_y, border_undefined);
+}
+
+void CLScharr3x3Kernel::configure(CLCompileContext &compile_context, const ICLTensor *input, ICLTensor *output_x, ICLTensor *output_y, bool border_undefined)
+{
     ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::U8);
     ARM_COMPUTE_ERROR_ON((output_x == nullptr) && (output_y == nullptr));
 
@@ -83,7 +88,7 @@
     }
 
     // Create kernel
-    _kernel = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel("scharr3x3", build_opts));
+    _kernel = create_kernel(compile_context, "scharr3x3", build_opts);
 
     // Configure kernel window
     constexpr unsigned int num_elems_processed_per_iteration = 8;
diff --git a/src/core/CL/kernels/CLSelectKernel.cpp b/src/core/CL/kernels/CLSelectKernel.cpp
index 5ee5405..866ec6b 100644
--- a/src/core/CL/kernels/CLSelectKernel.cpp
+++ b/src/core/CL/kernels/CLSelectKernel.cpp
@@ -104,6 +104,11 @@
 }
 void CLSelectKernel::configure(const ICLTensor *c, const ICLTensor *x, const ICLTensor *y, ICLTensor *output)
 {
+    configure(CLKernelLibrary::get().get_compile_context(), c, x, y, output);
+}
+
+void CLSelectKernel::configure(CLCompileContext &compile_context, const ICLTensor *c, const ICLTensor *x, const ICLTensor *y, ICLTensor *output)
+{
     ARM_COMPUTE_ERROR_ON_NULLPTR(c, x, y, output);
     ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(c->info(), x->info(), y->info(), output->info()));
 
@@ -141,7 +146,7 @@
         kernel_name += "_different_rank";
         kernel_name += is_input_rank_greater_than_two ? "_n" : "_2";
     }
-    _kernel = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel(kernel_name, build_opts.options()));
+    _kernel = create_kernel(compile_context, kernel_name, build_opts.options());
 
     // Configure kernel window
     auto win_config = validate_and_configure_window(c->info(), x->info(), y->info(), output->info());
diff --git a/src/core/CL/kernels/CLSobel3x3Kernel.cpp b/src/core/CL/kernels/CLSobel3x3Kernel.cpp
index 1186feb..1c97c13 100644
--- a/src/core/CL/kernels/CLSobel3x3Kernel.cpp
+++ b/src/core/CL/kernels/CLSobel3x3Kernel.cpp
@@ -50,6 +50,11 @@
 
 void CLSobel3x3Kernel::configure(const ICLTensor *input, ICLTensor *output_x, ICLTensor *output_y, bool border_undefined)
 {
+    configure(CLKernelLibrary::get().get_compile_context(), input, output_x, output_y, border_undefined);
+}
+
+void CLSobel3x3Kernel::configure(CLCompileContext &compile_context, const ICLTensor *input, ICLTensor *output_x, ICLTensor *output_y, bool border_undefined)
+{
     ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::U8);
     ARM_COMPUTE_ERROR_ON((output_x == nullptr) && (output_y == nullptr));
 
@@ -85,7 +90,7 @@
 
     // Create kernel
     const std::string kernel_name = std::string("sobel3x3");
-    _kernel                       = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel(kernel_name, build_opts));
+    _kernel                       = create_kernel(compile_context, kernel_name, build_opts);
 
     // Configure kernel window
     constexpr unsigned int num_elems_processed_per_iteration = 8;
diff --git a/src/core/CL/kernels/CLSobel5x5Kernel.cpp b/src/core/CL/kernels/CLSobel5x5Kernel.cpp
index cafdd98..5978077 100644
--- a/src/core/CL/kernels/CLSobel5x5Kernel.cpp
+++ b/src/core/CL/kernels/CLSobel5x5Kernel.cpp
@@ -50,6 +50,11 @@
 
 void CLSobel5x5HorKernel::configure(const ICLTensor *input, ICLTensor *output_x, ICLTensor *output_y, bool border_undefined)
 {
+    configure(CLKernelLibrary::get().get_compile_context(), input, output_x, output_y, border_undefined);
+}
+
+void CLSobel5x5HorKernel::configure(CLCompileContext &compile_context, const ICLTensor *input, ICLTensor *output_x, ICLTensor *output_y, bool border_undefined)
+{
     ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::U8);
     ARM_COMPUTE_ERROR_ON((output_x == nullptr) && (output_y == nullptr));
 
@@ -86,7 +91,7 @@
 
     // Create kernel
     const std::string kernel_name = std::string("sobel_separable1x5");
-    _kernel                       = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel(kernel_name, build_opts));
+    _kernel                       = create_kernel(compile_context, kernel_name, build_opts);
 
     // Configure kernel window
     constexpr unsigned int num_elems_processed_per_iteration = 8;
@@ -148,6 +153,11 @@
 
 void CLSobel5x5VertKernel::configure(const ICLTensor *input_x, const ICLTensor *input_y, ICLTensor *output_x, ICLTensor *output_y, bool border_undefined)
 {
+    configure(CLKernelLibrary::get().get_compile_context(), input_x, input_y, output_x, output_y, border_undefined);
+}
+
+void CLSobel5x5VertKernel::configure(CLCompileContext &compile_context, const ICLTensor *input_x, const ICLTensor *input_y, ICLTensor *output_x, ICLTensor *output_y, bool border_undefined)
+{
     ARM_COMPUTE_ERROR_ON((output_x == nullptr) && (output_y == nullptr));
 
     _run_sobel_x = output_x != nullptr;
@@ -185,7 +195,7 @@
 
     // Create kernel
     const std::string kernel_name = std::string("sobel_separable5x1");
-    _kernel                       = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel(kernel_name, build_opts));
+    _kernel                       = create_kernel(compile_context, kernel_name, build_opts);
 
     const ICLTensor *input = _run_sobel_x ? _input_x : _input_y;
 
diff --git a/src/core/CL/kernels/CLSobel7x7Kernel.cpp b/src/core/CL/kernels/CLSobel7x7Kernel.cpp
index 0c5bb58..183ebce 100644
--- a/src/core/CL/kernels/CLSobel7x7Kernel.cpp
+++ b/src/core/CL/kernels/CLSobel7x7Kernel.cpp
@@ -50,6 +50,11 @@
 
 void CLSobel7x7HorKernel::configure(const ICLTensor *input, ICLTensor *output_x, ICLTensor *output_y, bool border_undefined)
 {
+    configure(CLKernelLibrary::get().get_compile_context(), input, output_x, output_y, border_undefined);
+}
+
+void CLSobel7x7HorKernel::configure(CLCompileContext &compile_context, const ICLTensor *input, ICLTensor *output_x, ICLTensor *output_y, bool border_undefined)
+{
     ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::U8);
     ARM_COMPUTE_ERROR_ON((output_x == nullptr) && (output_y == nullptr));
 
@@ -88,7 +93,7 @@
     }
 
     // Create kernel
-    _kernel = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel(kernel_name, build_opts));
+    _kernel = create_kernel(compile_context, kernel_name, build_opts);
 
     // Configure kernel window
     constexpr unsigned int num_elems_processed_per_iteration = 8;
@@ -150,6 +155,11 @@
 
 void CLSobel7x7VertKernel::configure(const ICLTensor *input_x, const ICLTensor *input_y, ICLTensor *output_x, ICLTensor *output_y, bool border_undefined)
 {
+    configure(CLKernelLibrary::get().get_compile_context(), input_x, input_y, output_x, output_y, border_undefined);
+}
+
+void CLSobel7x7VertKernel::configure(CLCompileContext &compile_context, const ICLTensor *input_x, const ICLTensor *input_y, ICLTensor *output_x, ICLTensor *output_y, bool border_undefined)
+{
     ARM_COMPUTE_ERROR_ON((output_x == nullptr) && (output_y == nullptr));
 
     _run_sobel_x = output_x != nullptr;
@@ -187,7 +197,7 @@
 
     // Create kernel
     const std::string kernel_name = std::string("sobel_separable7x1");
-    _kernel                       = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel(kernel_name, build_opts));
+    _kernel                       = create_kernel(compile_context, kernel_name, build_opts);
 
     const ICLTensor *input = _run_sobel_x ? _input_x : _input_y;
 
diff --git a/src/core/CL/kernels/CLSoftmaxLayerKernel.cpp b/src/core/CL/kernels/CLSoftmaxLayerKernel.cpp
index d7a1778..112d864 100644
--- a/src/core/CL/kernels/CLSoftmaxLayerKernel.cpp
+++ b/src/core/CL/kernels/CLSoftmaxLayerKernel.cpp
@@ -220,6 +220,11 @@
 
 void CLLogits1DMaxShiftExpSumKernel::configure(const ICLTensor *input, ICLTensor *max, ICLTensor *output, ICLTensor *sum, const SoftmaxKernelInfo &info)
 {
+    configure(CLKernelLibrary::get().get_compile_context(), input, max, output, sum, info);
+}
+
+void CLLogits1DMaxShiftExpSumKernel::configure(CLCompileContext &compile_context, const ICLTensor *input, ICLTensor *max, ICLTensor *output, ICLTensor *sum, const SoftmaxKernelInfo &info)
+{
     ARM_COMPUTE_ERROR_ON_NULLPTR(input, max, sum, output);
 
     // Output auto initialization if not yet initialized
@@ -277,7 +282,7 @@
     }
 
     // Create kernel.
-    _kernel = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel(kernel_name, build_opts.options()));
+    _kernel = create_kernel(compile_context, kernel_name, build_opts.options());
 
     // Set static arguments. Both the kernels use the same arguments
     unsigned int idx = 4 * num_arguments_per_3D_tensor(); //Skip the input and output parameters
@@ -343,6 +348,11 @@
 
 void CLLogits1DNormKernel::configure(const ICLTensor *input, const ICLTensor *sum, ICLTensor *output, const SoftmaxKernelInfo &info)
 {
+    configure(CLKernelLibrary::get().get_compile_context(), input, sum, output, info);
+}
+
+void CLLogits1DNormKernel::configure(CLCompileContext &compile_context, const ICLTensor *input, const ICLTensor *sum, ICLTensor *output, const SoftmaxKernelInfo &info)
+{
     ARM_COMPUTE_ERROR_ON_NULLPTR(input, sum, output);
 
     // Note: output should always have a scale of 1/256 and offset 0
@@ -376,7 +386,7 @@
 
     // Create kernel
     std::string kernel_name = is_quantized_asymmetric ? "softmax_layer_norm_quantized" : "softmax_layer_norm";
-    _kernel                 = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel(kernel_name, build_opts.options()));
+    _kernel                 = create_kernel(compile_context, kernel_name, build_opts.options());
 
     // Configure window
     auto win_config = validate_and_configure_window_1DNorm(input->info(), output->info(), sum->info(), info);
diff --git a/src/core/CL/kernels/CLSpaceToBatchLayerKernel.cpp b/src/core/CL/kernels/CLSpaceToBatchLayerKernel.cpp
index 1b02eef..520924e 100644
--- a/src/core/CL/kernels/CLSpaceToBatchLayerKernel.cpp
+++ b/src/core/CL/kernels/CLSpaceToBatchLayerKernel.cpp
@@ -91,6 +91,11 @@
 
 void CLSpaceToBatchLayerKernel::configure(const ICLTensor *input, const ICLTensor *block_shape, const ICLTensor *paddings, ICLTensor *output)
 {
+    configure(CLKernelLibrary::get().get_compile_context(), input, block_shape, paddings, output);
+}
+
+void CLSpaceToBatchLayerKernel::configure(CLCompileContext &compile_context, const ICLTensor *input, const ICLTensor *block_shape, const ICLTensor *paddings, ICLTensor *output)
+{
     ARM_COMPUTE_ERROR_ON_NULLPTR(input, output);
     ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(input->info(), block_shape->info(), paddings->info(), output->info()));
 
@@ -113,7 +118,7 @@
     build_opts.add_option("-DWIDTH_IN=" + support::cpp11::to_string(input->info()->dimension(idx_width)));
     build_opts.add_option("-DHEIGHT_IN=" + support::cpp11::to_string(input->info()->dimension(idx_height)));
     build_opts.add_option("-DBATCH_IN=" + support::cpp11::to_string(input->info()->dimension(idx_batch)));
-    _kernel = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel("space_to_batch_" + lower_string(string_from_data_layout(input->info()->data_layout())), build_opts.options()));
+    _kernel = create_kernel(compile_context, "space_to_batch_" + lower_string(string_from_data_layout(input->info()->data_layout())), build_opts.options());
 
     // Configure kernel window
     Window win = calculate_max_window(*output->info(), Steps());
@@ -123,6 +128,13 @@
 void CLSpaceToBatchLayerKernel::configure(const ICLTensor *input, const int block_shape_x, const int block_shape_y, const Size2D &padding_left, const Size2D &padding_right,
                                           ICLTensor *output)
 {
+    configure(CLKernelLibrary::get().get_compile_context(), input, block_shape_x, block_shape_y, padding_left, padding_right, output);
+}
+
+void CLSpaceToBatchLayerKernel::configure(CLCompileContext &compile_context, const ICLTensor *input, const int block_shape_x, const int block_shape_y, const Size2D &padding_left,
+                                          const Size2D &padding_right,
+                                          ICLTensor    *output)
+{
     ARM_COMPUTE_ERROR_ON_NULLPTR(input, output);
 
     TensorShape output_shape = misc::shape_calculator::compute_space_to_batch_shape(input->info(), block_shape_x, block_shape_y, padding_left, padding_right);
@@ -153,7 +165,7 @@
     build_opts.add_option("-DPAD_RIGHT_X=" + support::cpp11::to_string(padding_right.x()));
     build_opts.add_option("-DPAD_LEFT_Y=" + support::cpp11::to_string(padding_left.y()));
     build_opts.add_option("-DPAD_RIGHT_Y=" + support::cpp11::to_string(padding_right.y()));
-    _kernel = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel("space_to_batch_static_" + lower_string(string_from_data_layout(input->info()->data_layout())), build_opts.options()));
+    _kernel = create_kernel(compile_context, "space_to_batch_static_" + lower_string(string_from_data_layout(input->info()->data_layout())), build_opts.options());
 
     // Configure kernel window
     Window win = calculate_max_window(*output->info(), Steps());
diff --git a/src/core/CL/kernels/CLSpaceToDepthLayerKernel.cpp b/src/core/CL/kernels/CLSpaceToDepthLayerKernel.cpp
index a7e3777..b4bd3b8 100644
--- a/src/core/CL/kernels/CLSpaceToDepthLayerKernel.cpp
+++ b/src/core/CL/kernels/CLSpaceToDepthLayerKernel.cpp
@@ -68,6 +68,11 @@
 
 void CLSpaceToDepthLayerKernel::configure(const ICLTensor *input, ICLTensor *output, int32_t block_shape)
 {
+    configure(CLKernelLibrary::get().get_compile_context(), input, output, block_shape);
+}
+
+void CLSpaceToDepthLayerKernel::configure(CLCompileContext &compile_context, const ICLTensor *input, ICLTensor *output, int32_t block_shape)
+{
     ARM_COMPUTE_ERROR_ON_NULLPTR(input, output);
 
     TensorShape output_shape = compute_depth_to_space_shape(input->info(), block_shape);
@@ -88,7 +93,7 @@
     build_opts.add_option("-DCHANNEL_SIZE=" + support::cpp11::to_string(output->info()->dimension(idx_channel)));
     build_opts.add_option("-DBLOCK_SHAPE=" + support::cpp11::to_string(block_shape));
     build_opts.add_option("-DWIDTH_IN=" + support::cpp11::to_string(output->info()->dimension(idx_width)));
-    _kernel = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel("space_to_depth_" + lower_string(string_from_data_layout(input->info()->data_layout())), build_opts.options()));
+    _kernel = create_kernel(compile_context, "space_to_depth_" + lower_string(string_from_data_layout(input->info()->data_layout())), build_opts.options());
 
     // Configure kernel window
     Window win = calculate_max_window(*output->info(), Steps());
diff --git a/src/core/CL/kernels/CLStackLayerKernel.cpp b/src/core/CL/kernels/CLStackLayerKernel.cpp
index 2da35d4..bc8645b 100644
--- a/src/core/CL/kernels/CLStackLayerKernel.cpp
+++ b/src/core/CL/kernels/CLStackLayerKernel.cpp
@@ -82,6 +82,11 @@
 
 void CLStackLayerKernel::configure(const ICLTensor *input, unsigned int axis, unsigned int idx_input, unsigned int num_tensors, ICLTensor *output)
 {
+    configure(CLKernelLibrary::get().get_compile_context(), input, axis, idx_input, num_tensors, output);
+}
+
+void CLStackLayerKernel::configure(CLCompileContext &compile_context, const ICLTensor *input, unsigned int axis, unsigned int idx_input, unsigned int num_tensors, ICLTensor *output)
+{
     ARM_COMPUTE_ERROR_ON_NULLPTR(input, output);
     ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(input->info(), axis, idx_input, num_tensors, output->info()));
 
@@ -99,7 +104,7 @@
     build_opts.add_option("-DDST_DIM3=" + support::cpp11::to_string(output->info()->dimension(3)));
 
     // Create kernel
-    _kernel = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel("stack_layer", build_opts.options()));
+    _kernel = create_kernel(compile_context, "stack_layer", build_opts.options());
 
     ARM_COMPUTE_ERROR_THROW_ON(win_config.first);
     ICLKernel::configure_internal(win_config.second);
diff --git a/src/core/CL/kernels/CLStridedSliceKernel.cpp b/src/core/CL/kernels/CLStridedSliceKernel.cpp
index 63478f1..99c0b0b 100644
--- a/src/core/CL/kernels/CLStridedSliceKernel.cpp
+++ b/src/core/CL/kernels/CLStridedSliceKernel.cpp
@@ -102,6 +102,13 @@
                                      const Coordinates &starts, const Coordinates &ends, const BiStrides &strides,
                                      int32_t begin_mask, int32_t end_mask, int32_t shrink_axis_mask)
 {
+    configure(CLKernelLibrary::get().get_compile_context(), input, output, starts, ends, strides, begin_mask, end_mask, shrink_axis_mask);
+}
+
+void CLStridedSliceKernel::configure(CLCompileContext &compile_context, const ICLTensor *input, ICLTensor *output,
+                                     const Coordinates &starts, const Coordinates &ends, const BiStrides &strides,
+                                     int32_t begin_mask, int32_t end_mask, int32_t shrink_axis_mask)
+{
     ARM_COMPUTE_ERROR_ON_NULLPTR(input, output);
     ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(input->info(), output->info(), starts, ends, strides, begin_mask, end_mask, shrink_axis_mask));
 
@@ -157,7 +164,7 @@
                                   "-DDST_DEPTH=1");
 
     // Create kernel
-    _kernel = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel("strided_slice", build_opts.options()));
+    _kernel = create_kernel(compile_context, "strided_slice", build_opts.options());
 
     // Set config_id for enabling LWS tuning
     _config_id = "strided_slice";
diff --git a/src/core/CL/kernels/CLTableLookupKernel.cpp b/src/core/CL/kernels/CLTableLookupKernel.cpp
index bbdaa37..f6c6ffb 100644
--- a/src/core/CL/kernels/CLTableLookupKernel.cpp
+++ b/src/core/CL/kernels/CLTableLookupKernel.cpp
@@ -1,5 +1,5 @@
 /*
- * Copyright (c) 2016, 2017 ARM Limited.
+ * Copyright (c) 2016-2020 ARM Limited.
  *
  * SPDX-License-Identifier: MIT
  *
@@ -38,6 +38,11 @@
 
 void CLTableLookupKernel::configure(const ICLTensor *input, const ICLLut *lut, ICLTensor *output)
 {
+    configure(CLKernelLibrary::get().get_compile_context(), input, lut, output);
+}
+
+void CLTableLookupKernel::configure(CLCompileContext &compile_context, const ICLTensor *input, const ICLLut *lut, ICLTensor *output)
+{
     ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::U8, DataType::S16);
     ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(output, 1, DataType::U8, DataType::S16);
     ARM_COMPUTE_ERROR_ON(lut == nullptr);
@@ -46,7 +51,7 @@
 
     // Create kernel
     std::string kernel_name = (DataType::S16 == lut->type()) ? "tablelookup_S16" : "tablelookup_U8";
-    _kernel                 = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel(kernel_name));
+    _kernel                 = create_kernel(compile_context, kernel_name);
 
     // Set lut argument
     unsigned int idx = 2 * num_arguments_per_2D_tensor(); //Skip the input and output parameters
diff --git a/src/core/CL/kernels/CLThresholdKernel.cpp b/src/core/CL/kernels/CLThresholdKernel.cpp
index 6e07cef..3a94fac 100644
--- a/src/core/CL/kernels/CLThresholdKernel.cpp
+++ b/src/core/CL/kernels/CLThresholdKernel.cpp
@@ -1,5 +1,5 @@
 /*
- * Copyright (c) 2016, 2017 ARM Limited.
+ * Copyright (c) 2016-2020 ARM Limited.
  *
  * SPDX-License-Identifier: MIT
  *
@@ -37,6 +37,12 @@
 void CLThresholdKernel::configure(const ICLTensor *input, ICLTensor *output, uint8_t threshold,
                                   uint8_t false_value, uint8_t true_value, ThresholdType type, uint8_t upper)
 {
+    configure(CLKernelLibrary::get().get_compile_context(), input, output, threshold, false_value, true_value, type, upper);
+}
+
+void CLThresholdKernel::configure(CLCompileContext &compile_context, const ICLTensor *input, ICLTensor *output, uint8_t threshold,
+                                  uint8_t false_value, uint8_t true_value, ThresholdType type, uint8_t upper)
+{
     ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::U8);
     ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(output, 1, DataType::U8);
 
@@ -57,7 +63,7 @@
     }
 
     // Create kernel
-    _kernel = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel(kernel_name));
+    _kernel = create_kernel(compile_context, kernel_name);
 
     // Set arguments
     unsigned int idx = 2 * num_arguments_per_2D_tensor(); //Skip the input and output parameters
diff --git a/src/core/CL/kernels/CLTileKernel.cpp b/src/core/CL/kernels/CLTileKernel.cpp
index b205e3a..5db69d3 100644
--- a/src/core/CL/kernels/CLTileKernel.cpp
+++ b/src/core/CL/kernels/CLTileKernel.cpp
@@ -69,6 +69,11 @@
 
 void CLTileKernel::configure(const ICLTensor *input, ICLTensor *output, const Multiples &multiples)
 {
+    configure(CLKernelLibrary::get().get_compile_context(), input, output, multiples);
+}
+
+void CLTileKernel::configure(CLCompileContext &compile_context, const ICLTensor *input, ICLTensor *output, const Multiples &multiples)
+{
     ARM_COMPUTE_ERROR_ON_NULLPTR(input, output);
 
     // Auto initialize output
@@ -97,7 +102,7 @@
     build_opts.add_option("-DDST_DEPTH=" + support::cpp11::to_string(output->info()->dimension(2)));
     build_opts.add_option_if(multi_access_x, "-DOFFSET=" + support::cpp11::to_string(offset));
     build_opts.add_option_if(multi_access_x, "-DVEC_SIZE=" + support::cpp11::to_string(vec_size_x));
-    _kernel = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel("tile", build_opts.options()));
+    _kernel = create_kernel(compile_context, "tile", build_opts.options());
 
     // Configure window without padding
     Window win = calculate_max_window(*output->info());
diff --git a/src/core/CL/kernels/CLTransposeKernel.cpp b/src/core/CL/kernels/CLTransposeKernel.cpp
index eb348ff..37f07e6 100644
--- a/src/core/CL/kernels/CLTransposeKernel.cpp
+++ b/src/core/CL/kernels/CLTransposeKernel.cpp
@@ -108,6 +108,11 @@
 
 void CLTransposeKernel::configure(const ICLTensor *input, ICLTensor *output)
 {
+    configure(CLKernelLibrary::get().get_compile_context(), input, output);
+}
+
+void CLTransposeKernel::configure(CLCompileContext &compile_context, const ICLTensor *input, ICLTensor *output)
+{
     ARM_COMPUTE_ERROR_ON_NULLPTR(input, output);
 
     // Output tensor auto inizialitation if not yet initialized
@@ -123,7 +128,7 @@
     data_type_in_bytes << input->info()->element_size();
     build_opts.emplace("-DDATA_TYPE_IN_BYTES=" + data_type_in_bytes.str());
 
-    _kernel = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel("transpose", build_opts));
+    _kernel = create_kernel(compile_context, "transpose", build_opts);
 
     // Configure kernel window
     auto win_config = validate_and_configure_window(input->info(), output->info());
diff --git a/src/core/CL/kernels/CLUpsampleLayerKernel.cpp b/src/core/CL/kernels/CLUpsampleLayerKernel.cpp
index a061236..8df6d5d 100644
--- a/src/core/CL/kernels/CLUpsampleLayerKernel.cpp
+++ b/src/core/CL/kernels/CLUpsampleLayerKernel.cpp
@@ -66,6 +66,11 @@
 
 void CLUpsampleLayerKernel::configure(const ICLTensor *input, ICLTensor *output, const Size2D &info, const InterpolationPolicy upsampling_policy)
 {
+    configure(CLKernelLibrary::get().get_compile_context(), input, output, info, upsampling_policy);
+}
+
+void CLUpsampleLayerKernel::configure(CLCompileContext &compile_context, const ICLTensor *input, ICLTensor *output, const Size2D &info, const InterpolationPolicy upsampling_policy)
+{
     ARM_COMPUTE_ERROR_ON_NULLPTR(input, output);
     ARM_COMPUTE_UNUSED(upsampling_policy);
 
@@ -126,7 +131,7 @@
     build_opts.add_option_if(multi_access_x, "-DVEC_SIZE_OUT=" + support::cpp11::to_string(num_elems_processed_per_iteration_x));
     build_opts.add_option_if(multi_access_x, "-DLAST_ACCESSED_X_IN=" + support::cpp11::to_string(std::max<int>(_input->info()->dimension(0) - _num_elems_processed_per_iteration_input_x, 0)));
     build_opts.add_option_if(multi_access_x, "-DLAST_ACCESSED_X_OUT=" + support::cpp11::to_string(std::max<int>(output_width_x - num_elems_processed_per_iteration_x, 0)));
-    _kernel = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel("upsample_layer_" + lower_string(string_from_data_layout(input->info()->data_layout())), build_opts.options()));
+    _kernel = create_kernel(compile_context, "upsample_layer_" + lower_string(string_from_data_layout(input->info()->data_layout())), build_opts.options());
 
     ICLKernel::configure_internal(win);
 }
diff --git a/src/core/CL/kernels/CLWarpAffineKernel.cpp b/src/core/CL/kernels/CLWarpAffineKernel.cpp
index 4aaa491..43bd34f 100644
--- a/src/core/CL/kernels/CLWarpAffineKernel.cpp
+++ b/src/core/CL/kernels/CLWarpAffineKernel.cpp
@@ -61,6 +61,11 @@
 
 void CLWarpAffineKernel::configure(const ICLTensor *input, ICLTensor *output, const std::array<float, 9> &matrix, InterpolationPolicy policy)
 {
+    configure(CLKernelLibrary::get().get_compile_context(), input, output, matrix, policy);
+}
+
+void CLWarpAffineKernel::configure(CLCompileContext &compile_context, const ICLTensor *input, ICLTensor *output, const std::array<float, 9> &matrix, InterpolationPolicy policy)
+{
     ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::U8);
     ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(output, 1, DataType::U8);
     ARM_COMPUTE_ERROR_ON(InterpolationPolicy::AREA == policy);
@@ -77,7 +82,7 @@
     std::string interpolation_name = string_from_interpolation_policy(policy);
     std::transform(interpolation_name.begin(), interpolation_name.end(), interpolation_name.begin(), ::tolower);
     const std::string kernel_name = "warp_affine_" + interpolation_name;
-    _kernel                       = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel(kernel_name, options));
+    _kernel                       = create_kernel(compile_context, kernel_name, options);
 
     // Set static kernel arguments
     unsigned int idx = 2 * num_arguments_per_2D_tensor(); //Skip the input and output parameters
diff --git a/src/core/CL/kernels/CLWarpPerspectiveKernel.cpp b/src/core/CL/kernels/CLWarpPerspectiveKernel.cpp
index e537aec..3c47567 100644
--- a/src/core/CL/kernels/CLWarpPerspectiveKernel.cpp
+++ b/src/core/CL/kernels/CLWarpPerspectiveKernel.cpp
@@ -1,5 +1,5 @@
 /*
- * Copyright (c) 2016-2018 ARM Limited.
+ * Copyright (c) 2016-2020 ARM Limited.
  *
  * SPDX-License-Identifier: MIT
  *
@@ -60,6 +60,11 @@
 
 void CLWarpPerspectiveKernel::configure(const ICLTensor *input, ICLTensor *output, const std::array<float, 9> &matrix, InterpolationPolicy policy)
 {
+    configure(CLKernelLibrary::get().get_compile_context(), input, output, matrix, policy);
+}
+
+void CLWarpPerspectiveKernel::configure(CLCompileContext &compile_context, const ICLTensor *input, ICLTensor *output, const std::array<float, 9> &matrix, InterpolationPolicy policy)
+{
     ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::U8);
     ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(output, 1, DataType::U8);
     ARM_COMPUTE_ERROR_ON(InterpolationPolicy::AREA == policy);
@@ -76,7 +81,7 @@
     std::string interpolation_name = string_from_interpolation_policy(policy);
     std::transform(interpolation_name.begin(), interpolation_name.end(), interpolation_name.begin(), ::tolower);
     std::string kernel_name = "warp_perspective_" + interpolation_name;
-    _kernel                 = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel(kernel_name, options));
+    _kernel                 = create_kernel(compile_context, kernel_name, options);
 
     // Set static kernel arguments
     unsigned int idx = 2 * num_arguments_per_2D_tensor(); //Skip the input and output parameters
diff --git a/src/core/CL/kernels/CLWeightsReshapeKernel.cpp b/src/core/CL/kernels/CLWeightsReshapeKernel.cpp
index 373cbe5..a0db660 100644
--- a/src/core/CL/kernels/CLWeightsReshapeKernel.cpp
+++ b/src/core/CL/kernels/CLWeightsReshapeKernel.cpp
@@ -79,6 +79,11 @@
 
 void CLWeightsReshapeKernel::configure(const ICLTensor *input, const ICLTensor *biases, ICLTensor *output, unsigned int num_groups)
 {
+    configure(CLKernelLibrary::get().get_compile_context(), input, biases, output, num_groups);
+}
+
+void CLWeightsReshapeKernel::configure(CLCompileContext &compile_context, const ICLTensor *input, const ICLTensor *biases, ICLTensor *output, unsigned int num_groups)
+{
     ARM_COMPUTE_ERROR_ON_NULLPTR(input, output);
 
     // Output tensor auto inizialitation if not yet initialized
@@ -102,7 +107,7 @@
     build_opts.add_option_if(biases != nullptr, "-DHAS_BIAS");
 
     // Create kernel
-    _kernel = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel("reshape_to_columns", build_opts.options()));
+    _kernel = create_kernel(compile_context, "reshape_to_columns", build_opts.options());
 
     // Configure window
     Window win = calculate_max_window(*input->info(), Steps());
diff --git a/src/core/CL/kernels/CLWidthConcatenate2TensorsKernel.cpp b/src/core/CL/kernels/CLWidthConcatenate2TensorsKernel.cpp
index 4d52f09..ea549e9 100644
--- a/src/core/CL/kernels/CLWidthConcatenate2TensorsKernel.cpp
+++ b/src/core/CL/kernels/CLWidthConcatenate2TensorsKernel.cpp
@@ -96,6 +96,11 @@
 
 void CLWidthConcatenate2TensorsKernel::configure(const ICLTensor *input1, const ICLTensor *input2, ICLTensor *output)
 {
+    configure(CLKernelLibrary::get().get_compile_context(), input1, input2, output);
+}
+
+void CLWidthConcatenate2TensorsKernel::configure(CLCompileContext &compile_context, const ICLTensor *input1, const ICLTensor *input2, ICLTensor *output)
+{
     ARM_COMPUTE_ERROR_ON_NULLPTR(input1, input2, output);
     ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(input1->info(), input2->info(), output->info()));
 
@@ -128,7 +133,7 @@
     }
 
     // Create kernel
-    _kernel = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel("concatenate_width_x2", build_opts.options()));
+    _kernel = create_kernel(compile_context, "concatenate_width_x2", build_opts.options());
 
     // Configure kernel window
     auto win_config = validate_and_configure_window(input1->info(), input2->info(), output->info());
diff --git a/src/core/CL/kernels/CLWidthConcatenate4TensorsKernel.cpp b/src/core/CL/kernels/CLWidthConcatenate4TensorsKernel.cpp
index 0673365..e1ec9d1 100644
--- a/src/core/CL/kernels/CLWidthConcatenate4TensorsKernel.cpp
+++ b/src/core/CL/kernels/CLWidthConcatenate4TensorsKernel.cpp
@@ -114,6 +114,12 @@
 
 void CLWidthConcatenate4TensorsKernel::configure(const ICLTensor *input1, const ICLTensor *input2, const ICLTensor *input3, const ICLTensor *input4, ICLTensor *output)
 {
+    configure(CLKernelLibrary::get().get_compile_context(), input1, input2, input3, input4, output);
+}
+
+void CLWidthConcatenate4TensorsKernel::configure(CLCompileContext &compile_context, const ICLTensor *input1, const ICLTensor *input2, const ICLTensor *input3, const ICLTensor *input4,
+                                                 ICLTensor *output)
+{
     ARM_COMPUTE_ERROR_ON_NULLPTR(input1, input2, input3, input4, output);
     ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(input1->info(), input2->info(), input3->info(), input4->info(), output->info()));
 
@@ -156,7 +162,7 @@
     }
 
     // Create kernel
-    _kernel = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel("concatenate_width_x4", build_opts.options()));
+    _kernel = create_kernel(compile_context, "concatenate_width_x4", build_opts.options());
 
     // Configure kernel window
     auto win_config = validate_and_configure_window(input1->info(), input2->info(), input3->info(), input4->info(), output->info());
diff --git a/src/core/CL/kernels/CLWidthConcatenateLayerKernel.cpp b/src/core/CL/kernels/CLWidthConcatenateLayerKernel.cpp
index eaefe66..9ff373b 100644
--- a/src/core/CL/kernels/CLWidthConcatenateLayerKernel.cpp
+++ b/src/core/CL/kernels/CLWidthConcatenateLayerKernel.cpp
@@ -92,6 +92,11 @@
 
 void CLWidthConcatenateLayerKernel::configure(const ICLTensor *input, unsigned int width_offset, ICLTensor *output)
 {
+    configure(CLKernelLibrary::get().get_compile_context(), input, width_offset, output);
+}
+
+void CLWidthConcatenateLayerKernel::configure(CLCompileContext &compile_context, const ICLTensor *input, unsigned int width_offset, ICLTensor *output)
+{
     ARM_COMPUTE_ERROR_ON_NULLPTR(input, output);
     ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(input->info(), width_offset, output->info()));
 
@@ -118,7 +123,7 @@
     }
 
     // Create kernel
-    _kernel = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel("concatenate_width", build_opts.options()));
+    _kernel = create_kernel(compile_context, "concatenate_width", build_opts.options());
     // Configure kernel window
     auto win_config = validate_and_configure_window(input->info(), width_offset, output->info());
     ARM_COMPUTE_ERROR_THROW_ON(std::get<0>(win_config));
diff --git a/src/core/CL/kernels/CLWinogradFilterTransformKernel.cpp b/src/core/CL/kernels/CLWinogradFilterTransformKernel.cpp
index b4135f2..3864912 100644
--- a/src/core/CL/kernels/CLWinogradFilterTransformKernel.cpp
+++ b/src/core/CL/kernels/CLWinogradFilterTransformKernel.cpp
@@ -101,6 +101,11 @@
 
 void CLWinogradFilterTransformKernel::configure(const ICLTensor *input, ICLTensor *output, const WinogradInfo &winograd_info)
 {
+    configure(CLKernelLibrary::get().get_compile_context(), input, output, winograd_info);
+}
+
+void CLWinogradFilterTransformKernel::configure(CLCompileContext &compile_context, const ICLTensor *input, ICLTensor *output, const WinogradInfo &winograd_info)
+{
     ARM_COMPUTE_ERROR_ON_NULLPTR(input, output);
 
     // Output auto initialization if not yet initialized
@@ -119,7 +124,7 @@
 
     // Create kernel
     std::string kernel_name = "winograd_filter_transform_" + output_tile_size.to_string() + "_" + kernel_size.to_string() + "_" + lower_string(string_from_data_layout(input->info()->data_layout()));
-    _kernel                 = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel(kernel_name, build_opts.options()));
+    _kernel                 = create_kernel(compile_context, kernel_name, build_opts.options());
 
     _input  = input;
     _output = output;
diff --git a/src/core/CL/kernels/CLWinogradInputTransformKernel.cpp b/src/core/CL/kernels/CLWinogradInputTransformKernel.cpp
index 5b76a3d..cf882ae 100644
--- a/src/core/CL/kernels/CLWinogradInputTransformKernel.cpp
+++ b/src/core/CL/kernels/CLWinogradInputTransformKernel.cpp
@@ -110,6 +110,11 @@
 
 void CLWinogradInputTransformKernel::configure(const ICLTensor *input, ICLTensor *output, const WinogradInfo &winograd_info)
 {
+    configure(CLKernelLibrary::get().get_compile_context(), input, output, winograd_info);
+}
+
+void CLWinogradInputTransformKernel::configure(CLCompileContext &compile_context, const ICLTensor *input, ICLTensor *output, const WinogradInfo &winograd_info)
+{
     ARM_COMPUTE_ERROR_ON_NULLPTR(input, output);
     ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(input->info(), output->info(), winograd_info));
 
@@ -195,7 +200,7 @@
     kernel_name += support::cpp11::to_string(_step_z);
     kernel_name += "_" + lower_string(string_from_data_layout(_data_layout));
 
-    _kernel = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel(kernel_name, build_opts.options()));
+    _kernel = create_kernel(compile_context, kernel_name, build_opts.options());
 
     // Create window and update padding
     auto win_config = validate_and_configure_window(input->info(), output->info(), winograd_info);
diff --git a/src/core/CL/kernels/CLWinogradOutputTransformKernel.cpp b/src/core/CL/kernels/CLWinogradOutputTransformKernel.cpp
index 0bd3b28..f08b5ac 100644
--- a/src/core/CL/kernels/CLWinogradOutputTransformKernel.cpp
+++ b/src/core/CL/kernels/CLWinogradOutputTransformKernel.cpp
@@ -137,6 +137,12 @@
 
 void CLWinogradOutputTransformKernel::configure(const ICLTensor *input, const ICLTensor *bias, ICLTensor *output, const WinogradInfo &winograd_info, const ActivationLayerInfo &act_info)
 {
+    configure(CLKernelLibrary::get().get_compile_context(), input, bias, output, winograd_info, act_info);
+}
+
+void CLWinogradOutputTransformKernel::configure(CLCompileContext &compile_context, const ICLTensor *input, const ICLTensor *bias, ICLTensor *output, const WinogradInfo &winograd_info,
+                                                const ActivationLayerInfo &act_info)
+{
     ARM_COMPUTE_ERROR_ON_NULLPTR(input, output);
 
     // Output tensor auto initialization if not yet initialized
@@ -188,7 +194,7 @@
 
     // Create kernel
     std::string kernel_name = "winograd_output_transform_" + output_tile_size.to_string() + "_" + kernel_size.to_string() + "_" + lower_string(string_from_data_layout(winograd_info.output_data_layout));
-    _kernel                 = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel(kernel_name, build_opts.options()));
+    _kernel                 = create_kernel(compile_context, kernel_name, build_opts.options());
 
     // Configure kernel window
     auto win_config = validate_and_configure_window(input->info(), (bias != nullptr ? bias->info() : nullptr), output->info(), winograd_info.output_tile_size);
diff --git a/src/core/CL/kernels/CLYOLOLayerKernel.cpp b/src/core/CL/kernels/CLYOLOLayerKernel.cpp
index f634d91..ee11923 100644
--- a/src/core/CL/kernels/CLYOLOLayerKernel.cpp
+++ b/src/core/CL/kernels/CLYOLOLayerKernel.cpp
@@ -102,6 +102,11 @@
 
 void CLYOLOLayerKernel::configure(ICLTensor *input, ICLTensor *output, const ActivationLayerInfo &act_info, int32_t num_classes)
 {
+    configure(CLKernelLibrary::get().get_compile_context(), input, output, act_info, num_classes);
+}
+
+void CLYOLOLayerKernel::configure(CLCompileContext &compile_context, ICLTensor *input, ICLTensor *output, const ActivationLayerInfo &act_info, int32_t num_classes)
+{
     ARM_COMPUTE_ERROR_ON_NULLPTR(input);
 
     _run_in_place = (output == nullptr) || (output == input);
@@ -127,7 +132,7 @@
 
     // Create kernel
     std::string kernel_name = std::string("yolo_layer_") + lower_string(string_from_data_layout(input->info()->data_layout()));
-    _kernel                 = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel(kernel_name, build_opts.options()));
+    _kernel                 = create_kernel(compile_context, kernel_name, build_opts.options());
 
     // Make sure _kernel is initialized before calling the parent's configure
     _input  = input;
diff --git a/src/runtime/CL/functions/CLActivationLayer.cpp b/src/runtime/CL/functions/CLActivationLayer.cpp
index 0b29fe1..9882145 100644
--- a/src/runtime/CL/functions/CLActivationLayer.cpp
+++ b/src/runtime/CL/functions/CLActivationLayer.cpp
@@ -37,9 +37,7 @@
 
 void CLActivationLayer::configure(ICLTensor *input, ICLTensor *output, ActivationLayerInfo act_info)
 {
-    auto core_ctx = _ctx ? _ctx->core_runtime_context() : /* Legacy */ nullptr;
-
-    auto k = arm_compute::support::cpp14::make_unique<CLActivationLayerKernel>(core_ctx);
+    auto k = arm_compute::support::cpp14::make_unique<CLActivationLayerKernel>();
     k->configure(input, output, act_info);
     _kernel = std::move(k);
 }