diff --git a/src/runtime/CL/CLOperator.cpp b/src/runtime/CL/CLOperator.cpp
new file mode 100644
index 0000000..8dc05d8
--- /dev/null
+++ b/src/runtime/CL/CLOperator.cpp
@@ -0,0 +1,53 @@
+/*
+ * Copyright (c) 2020 ARM Limited.
+ *
+ * SPDX-License-Identifier: MIT
+ *
+ * Permission is hereby granted, free of charge, to any person obtaining a copy
+ * of this software and associated documentation files (the "Software"), to
+ * deal in the Software without restriction, including without limitation the
+ * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or
+ * sell copies of the Software, and to permit persons to whom the Software is
+ * furnished to do so, subject to the following conditions:
+ *
+ * The above copyright notice and this permission notice shall be included in all
+ * copies or substantial portions of the Software.
+ *
+ * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+ * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+ * FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+ * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+ * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+ * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
+ * SOFTWARE.
+ */
+#include "arm_compute/runtime/CL/CLScheduler.h"
+#include "arm_compute/runtime/CL/ICLOperator.h"
+
+namespace arm_compute
+{
+namespace experimental
+{
+ICLOperator::ICLOperator(IRuntimeContext *ctx)
+    : _kernel(), _ctx(ctx), _workspace()
+{
+}
+
+void ICLOperator::run(InputTensorMap inputs, OutputTensorMap outputs, OperatorTensorMap workspace)
+{
+    ARM_COMPUTE_UNUSED(workspace);
+
+    if(inputs.empty() || outputs.empty())
+    {
+        ARM_COMPUTE_ERROR("No inputs provided");
+    }
+
+    CLScheduler::get().enqueue_op(*_kernel.get(), inputs, outputs, false);
+}
+
+void ICLOperator::prepare(OperatorTensorMap constants)
+{
+    ARM_COMPUTE_UNUSED(constants);
+}
+} // namespace experimental
+} // namespace arm_compute
diff --git a/src/runtime/CL/CLScheduler.cpp b/src/runtime/CL/CLScheduler.cpp
index e78eaa4..2c1024f 100644
--- a/src/runtime/CL/CLScheduler.cpp
+++ b/src/runtime/CL/CLScheduler.cpp
@@ -1,5 +1,5 @@
 /*
- * Copyright (c) 2016-2019 ARM Limited.
+ * Copyright (c) 2016-2020 ARM Limited.
  *
  * SPDX-License-Identifier: MIT
  *
@@ -151,7 +151,7 @@
     _cl_tuner       = cl_tuner;
 }
 
-void CLScheduler::enqueue(ICLKernel &kernel, bool flush)
+void CLScheduler::enqueue_common(ICLKernel &kernel, const InputTensorMap &inputs, const OutputTensorMap &outputs, bool flush)
 {
     ARM_COMPUTE_ERROR_ON_MSG(!_is_initialised,
                              "The CLScheduler is not initialised yet! Please call the CLScheduler::get().default_init(), \
@@ -165,11 +165,28 @@
     }
 
     // Run kernel
-    kernel.run(kernel.window(), _queue);
+    if(inputs.empty())
+    {
+        kernel.run(kernel.window(), _queue);
+    }
+    else
+    {
+        kernel.run_op(inputs, outputs, kernel.window(), _queue);
+    }
 
     if(flush)
     {
         _queue.flush();
     }
 }
+
+void CLScheduler::enqueue(ICLKernel &kernel, bool flush)
+{
+    enqueue_common(kernel, {}, {}, flush);
+}
+
+void CLScheduler::enqueue_op(ICLKernel &kernel, const InputTensorMap &inputs, const OutputTensorMap &outputs, bool flush)
+{
+    enqueue_common(kernel, inputs, outputs, flush);
+}
 } // namespace arm_compute
diff --git a/src/runtime/CL/functions/CLArgMinMaxLayer.cpp b/src/runtime/CL/functions/CLArgMinMaxLayer.cpp
index cb2b290..8fcd04f 100644
--- a/src/runtime/CL/functions/CLArgMinMaxLayer.cpp
+++ b/src/runtime/CL/functions/CLArgMinMaxLayer.cpp
@@ -35,7 +35,7 @@
 namespace arm_compute
 {
 CLArgMinMaxLayer::CLArgMinMaxLayer(std::shared_ptr<IMemoryManager> memory_manager)
-    : _memory_group(std::move(memory_manager)), _results_vector(), _not_reshaped_output(), _reduction_kernels_vector(), _reshape_kernel(), _num_of_stages(), _reduction_axis()
+    : _memory_group(std::move(memory_manager)), _results_vector(), _not_reshaped_output(), _reduction_kernels_vector(), _reshape(), _num_of_stages(), _reduction_axis()
 {
 }
 
@@ -103,7 +103,7 @@
         const unsigned int last_stage = num_of_stages - 1;
         ARM_COMPUTE_RETURN_ON_ERROR(CLArgMinMaxLayerKernel::validate(input, &sums_vector[last_stage - 1], &not_reshaped_output, axis, op));
     }
-    ARM_COMPUTE_RETURN_ON_ERROR(CLReshapeLayerKernel::validate(&not_reshaped_output, output));
+    ARM_COMPUTE_RETURN_ON_ERROR(CLReshapeLayer::validate(&not_reshaped_output, output));
     return Status{};
 }
 
@@ -158,7 +158,7 @@
         _reduction_kernels_vector[last_stage].configure(compile_context, input, &_results_vector[last_stage - 1], &_not_reshaped_output, axis, op);
         _results_vector[last_stage - 1].allocator()->allocate();
     }
-    _reshape_kernel.configure(compile_context, &_not_reshaped_output, output);
+    _reshape.configure(compile_context, &_not_reshaped_output, output);
     _not_reshaped_output.allocator()->allocate();
 }
 
@@ -170,6 +170,6 @@
     {
         CLScheduler::get().enqueue(_reduction_kernels_vector[i], false);
     }
-    CLScheduler::get().enqueue(_reshape_kernel, false);
+    _reshape.run();
 }
 } // namespace arm_compute
\ No newline at end of file
diff --git a/src/runtime/CL/functions/CLGenerateProposalsLayer.cpp b/src/runtime/CL/functions/CLGenerateProposalsLayer.cpp
index 7f037fc..1b89bb4 100644
--- a/src/runtime/CL/functions/CLGenerateProposalsLayer.cpp
+++ b/src/runtime/CL/functions/CLGenerateProposalsLayer.cpp
@@ -31,9 +31,9 @@
 CLGenerateProposalsLayer::CLGenerateProposalsLayer(std::shared_ptr<IMemoryManager> memory_manager)
     : _memory_group(memory_manager),
       _permute_deltas_kernel(),
-      _flatten_deltas_kernel(),
+      _flatten_deltas(),
       _permute_scores_kernel(),
-      _flatten_scores_kernel(),
+      _flatten_scores(),
       _compute_anchors_kernel(),
       _bounding_box_kernel(),
       _pad_kernel(),
@@ -102,12 +102,12 @@
     {
         _memory_group.manage(&_deltas_permuted);
         _permute_deltas_kernel.configure(compile_context, deltas, &_deltas_permuted, PermutationVector{ 2, 0, 1 });
-        _flatten_deltas_kernel.configure(compile_context, &_deltas_permuted, &_deltas_flattened);
+        _flatten_deltas.configure(compile_context, &_deltas_permuted, &_deltas_flattened);
         _deltas_permuted.allocator()->allocate();
     }
     else
     {
-        _flatten_deltas_kernel.configure(compile_context, deltas, &_deltas_flattened);
+        _flatten_deltas.configure(compile_context, deltas, &_deltas_flattened);
     }
 
     const TensorShape flatten_shape_scores(1, total_num_anchors);
@@ -119,12 +119,12 @@
     {
         _memory_group.manage(&_scores_permuted);
         _permute_scores_kernel.configure(compile_context, scores, &_scores_permuted, PermutationVector{ 2, 0, 1 });
-        _flatten_scores_kernel.configure(compile_context, &_scores_permuted, &_scores_flattened);
+        _flatten_scores.configure(compile_context, &_scores_permuted, &_scores_flattened);
         _scores_permuted.allocator()->allocate();
     }
     else
     {
-        _flatten_scores_kernel.configure(compile_context, scores, &_scores_flattened);
+        _flatten_scores.configure(compile_context, scores, &_scores_flattened);
     }
 
     CLTensor *anchors_to_use = &_all_anchors;
@@ -240,12 +240,12 @@
     }
 
     TensorInfo deltas_flattened_info(deltas->clone()->set_tensor_shape(TensorShape(values_per_roi, total_num_anchors)).set_is_resizable(true));
-    ARM_COMPUTE_RETURN_ON_ERROR(CLReshapeLayerKernel::validate(&deltas_permuted_info, &deltas_flattened_info));
+    ARM_COMPUTE_RETURN_ON_ERROR(CLReshapeLayer::validate(&deltas_permuted_info, &deltas_flattened_info));
 
     TensorInfo scores_flattened_info(scores->clone()->set_tensor_shape(TensorShape(1, total_num_anchors)).set_is_resizable(true));
     TensorInfo proposals_4_roi_values(deltas->clone()->set_tensor_shape(TensorShape(values_per_roi, total_num_anchors)).set_is_resizable(true));
 
-    ARM_COMPUTE_RETURN_ON_ERROR(CLReshapeLayerKernel::validate(&scores_permuted_info, &scores_flattened_info));
+    ARM_COMPUTE_RETURN_ON_ERROR(CLReshapeLayer::validate(&scores_permuted_info, &scores_flattened_info));
 
     TensorInfo *proposals_4_roi_values_to_use = &proposals_4_roi_values;
     TensorInfo  proposals_4_roi_values_quantized(deltas->clone()->set_tensor_shape(TensorShape(values_per_roi, total_num_anchors)).set_is_resizable(true));
@@ -350,8 +350,8 @@
         CLScheduler::get().enqueue(_permute_deltas_kernel, false);
         CLScheduler::get().enqueue(_permute_scores_kernel, false);
     }
-    CLScheduler::get().enqueue(_flatten_deltas_kernel, false);
-    CLScheduler::get().enqueue(_flatten_scores_kernel, false);
+    _flatten_deltas.run();
+    _flatten_scores.run();
 
     if(_is_qasymm8)
     {
diff --git a/src/runtime/CL/functions/CLReductionOperation.cpp b/src/runtime/CL/functions/CLReductionOperation.cpp
index b659ecf..2d7db0a 100644
--- a/src/runtime/CL/functions/CLReductionOperation.cpp
+++ b/src/runtime/CL/functions/CLReductionOperation.cpp
@@ -39,7 +39,7 @@
 namespace arm_compute
 {
 CLReductionOperation::CLReductionOperation(std::shared_ptr<IMemoryManager> memory_manager)
-    : _memory_group(std::move(memory_manager)), _results_vector(), _reduction_kernels_vector(), _border_handlers_vector(), _reshape_kernel(), _op(), _num_of_stages(), _reduction_axis(), _is_serial(),
+    : _memory_group(std::move(memory_manager)), _results_vector(), _reduction_kernels_vector(), _border_handlers_vector(), _reshape(), _op(), _num_of_stages(), _reduction_axis(), _is_serial(),
       _is_reshape_required(false)
 {
 }
@@ -152,7 +152,7 @@
 
     if(is_reshape_required)
     {
-        ARM_COMPUTE_RETURN_ON_ERROR(CLReshapeLayerKernel::validate(output_internal, output));
+        ARM_COMPUTE_RETURN_ON_ERROR(CLReshapeLayer::validate(output_internal, output));
     }
 
     return Status{};
@@ -351,7 +351,7 @@
 
     if(_is_reshape_required)
     {
-        _reshape_kernel.configure(compile_context, &_results_vector.back(), output);
+        _reshape.configure(compile_context, &_results_vector.back(), output);
         _results_vector.back().allocator()->allocate();
     }
 }
@@ -375,7 +375,7 @@
 
     if(_is_reshape_required)
     {
-        CLScheduler::get().enqueue(_reshape_kernel, false);
+        _reshape.run();
     }
 }
 } // namespace arm_compute
diff --git a/src/runtime/CL/functions/CLReshapeLayer.cpp b/src/runtime/CL/functions/CLReshapeLayer.cpp
index 13baedb..6fc8608 100644
--- a/src/runtime/CL/functions/CLReshapeLayer.cpp
+++ b/src/runtime/CL/functions/CLReshapeLayer.cpp
@@ -28,14 +28,11 @@
 #include "support/MemorySupport.h"
 
 /** [CLReshapeLayer snippet] **/
-using namespace arm_compute;
-
-void CLReshapeLayer::configure(const ICLTensor *input, ICLTensor *output)
+namespace arm_compute
 {
-    configure(CLKernelLibrary::get().get_compile_context(), input, output);
-}
-
-void CLReshapeLayer::configure(const CLCompileContext &compile_context, const ICLTensor *input, ICLTensor *output)
+namespace experimental
+{
+void CLReshapeLayer::configure(const CLCompileContext &compile_context, const ITensorInfo *input, ITensorInfo *output)
 {
     auto k = arm_compute::support::cpp14::make_unique<CLReshapeLayerKernel>();
     k->configure(compile_context, input, output);
@@ -44,6 +41,58 @@
 
 Status CLReshapeLayer::validate(const ITensorInfo *input, const ITensorInfo *output)
 {
-    return CLReshapeLayerKernel::validate(input, output);
+    return arm_compute::CLReshapeLayerKernel::validate(input, output);
 }
+
+MemoryRequirements CLReshapeLayer::workspace() const
+{
+    return MemoryRequirements{};
+}
+} // namespace experimental
+
+struct CLReshapeLayer::Impl
+{
+    const ICLTensor                              *src{ nullptr };
+    ICLTensor                                    *dst{ nullptr };
+    std::unique_ptr<experimental::CLReshapeLayer> op{ nullptr };
+};
+
+CLReshapeLayer::CLReshapeLayer()
+    : _impl(support::cpp14::make_unique<Impl>())
+{
+}
+
+CLReshapeLayer::CLReshapeLayer(CLReshapeLayer &&) = default;
+CLReshapeLayer &CLReshapeLayer::operator=(CLReshapeLayer &&) = default;
+CLReshapeLayer::~CLReshapeLayer()                            = default;
+
+void CLReshapeLayer::configure(const ICLTensor *input, ICLTensor *output)
+{
+    configure(CLKernelLibrary::get().get_compile_context(), input, output);
+}
+
+void CLReshapeLayer::configure(const CLCompileContext &compile_context, const ICLTensor *input, ICLTensor *output)
+{
+    _impl->src = input;
+    _impl->dst = output;
+    _impl->op  = arm_compute::support::cpp14::make_unique<experimental::CLReshapeLayer>();
+    _impl->op->configure(compile_context, input->info(), output->info());
+}
+
+Status CLReshapeLayer::validate(const ITensorInfo *input, const ITensorInfo *output)
+{
+    ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(input, output);
+    ARM_COMPUTE_RETURN_ON_ERROR(experimental::CLReshapeLayer::validate(input, output));
+
+    return Status{};
+}
+
+void CLReshapeLayer::run()
+{
+    const InputTensorMap  src{ { TensorType::ACL_SRC, _impl->src } };
+    const OutputTensorMap dst{ { TensorType::ACL_DST, _impl->dst } };
+
+    _impl->op->run(src, dst, {});
+}
+} // namespace arm_compute
 /** [CLReshapeLayer snippet] **/
diff --git a/src/runtime/CL/functions/CLSoftmaxLayer.cpp b/src/runtime/CL/functions/CLSoftmaxLayer.cpp
index 71ccf9f..52fac4f 100644
--- a/src/runtime/CL/functions/CLSoftmaxLayer.cpp
+++ b/src/runtime/CL/functions/CLSoftmaxLayer.cpp
@@ -36,7 +36,7 @@
 {
 template <bool IS_LOG>
 CLSoftmaxLayerGeneric<IS_LOG>::CLSoftmaxLayerGeneric(std::shared_ptr<IMemoryManager> memory_manager)
-    : _memory_group(std::move(memory_manager)), _max_shift_exp_sum_kernel(), _norm_kernel(), _flatten_kernel_ptr(), _reshape_kernel(), _max(), _sum(), _tmp(), _input_flattened(), _output_flattened(),
+    : _memory_group(std::move(memory_manager)), _max_shift_exp_sum_kernel(), _norm_kernel(), _flatten_ptr(), _reshape(), _max(), _sum(), _tmp(), _input_flattened(), _output_flattened(),
       _needs_flattening(false)
 {
 }
@@ -64,15 +64,15 @@
     //   2. first_n_reduce_axes == 4: Reduce all 4 dimensions. This can only be handled by CLReshapeKernel instead of CLFlattenKernel.
     if(first_n_reduce_axes == 3)
     {
-        auto flatten_kernel_ptr = support::cpp14::make_unique<CLFlattenLayerKernel>();
-        flatten_kernel_ptr->configure(compile_context, input, &_input_flattened);
-        _flatten_kernel_ptr = std::move(flatten_kernel_ptr);
+        auto flatten = support::cpp14::make_unique<CLFlattenLayer>();
+        flatten->configure(compile_context, input, &_input_flattened);
+        _flatten_ptr = std::move(flatten);
     }
     else
     {
-        auto reshape_kernel_ptr = support::cpp14::make_unique<CLReshapeLayerKernel>();
-        reshape_kernel_ptr->configure(compile_context, input, &_input_flattened);
-        _flatten_kernel_ptr = std::move(reshape_kernel_ptr);
+        auto reshape_ptr = support::cpp14::make_unique<CLReshapeLayer>();
+        reshape_ptr->configure(compile_context, input, &_input_flattened);
+        _flatten_ptr = std::move(reshape_ptr);
     }
 
     // We need to init the output tensor here. Indeed, the reshape kernel expects
@@ -152,7 +152,7 @@
         _norm_kernel.configure(compile_context, &_tmp, &_sum, &_output_flattened, softmax_info);
 
         // Reshape the flat output into a the requested (4D) output
-        _reshape_kernel.configure(compile_context, &_output_flattened, output);
+        _reshape.configure(compile_context, &_output_flattened, output);
 
         // Allocate the intermediate flat tensors
         _input_flattened.allocator()->allocate();
@@ -199,11 +199,11 @@
 
         if(first_n_reduce_axes == 3)
         {
-            ARM_COMPUTE_RETURN_ON_ERROR(CLFlattenLayerKernel::validate(input, &tensor_info_flat));
+            ARM_COMPUTE_RETURN_ON_ERROR(CLFlattenLayer::validate(input, &tensor_info_flat));
         }
         else
         {
-            ARM_COMPUTE_RETURN_ON_ERROR(CLReshapeLayerKernel::validate(input, &tensor_info_flat));
+            ARM_COMPUTE_RETURN_ON_ERROR(CLReshapeLayer::validate(input, &tensor_info_flat));
         }
     }
 
@@ -231,7 +231,7 @@
 
     if(_needs_flattening)
     {
-        CLScheduler::get().enqueue(*_flatten_kernel_ptr, false);
+        _flatten_ptr->run();
     }
 
     CLScheduler::get().enqueue(_max_shift_exp_sum_kernel, false);
@@ -239,7 +239,7 @@
 
     if(_needs_flattening)
     {
-        CLScheduler::get().enqueue(_reshape_kernel, true);
+        _reshape.run();
     }
 }