COMPMID-748 - Integrating optimized SGEMM for bifrost

This patch introduces a new GEMM capable to improve the mac utilisation
of 10% compared to the GEMM without reshape. However this implementation
is not faster in all cases as we need to take into account the time for
reshaping the matrices. For this reason an heuristic solution to select
the optimal GEMM to use has been added to the function. More information
about the heuristic implementation can be found at COMPMID-852.
With this new patch, GoogleNet, MobileNet, VGG16 and SqueezeNet can
improved the performance of 1.5x.
More information about the performance uplift can be found here:
https://confluence.arm.com/display/MLENG/GEMM+FP32+performance%3A+ACL+18.02

Change-Id: I024563c06b9aed02a211a974e452bae5c233b04c
Reviewed-on: https://eu-gerrit-1.euhpc.arm.com/117140
Reviewed-by: Pablo Tello <pablo.tello@arm.com>
Tested-by: Jenkins <bsgcomp@arm.com>
Reviewed-by: Anthony Barbier <anthony.barbier@arm.com>
diff --git a/arm_compute/core/CL/kernels/CLGEMMInterleave4x4Kernel.h b/arm_compute/core/CL/kernels/CLGEMMInterleave4x4Kernel.h
index 2520eff..c0fef45 100644
--- a/arm_compute/core/CL/kernels/CLGEMMInterleave4x4Kernel.h
+++ b/arm_compute/core/CL/kernels/CLGEMMInterleave4x4Kernel.h
@@ -1,5 +1,5 @@
 /*
- * Copyright (c) 2017 ARM Limited.
+ * Copyright (c) 2017-2018 ARM Limited.
  *
  * SPDX-License-Identifier: MIT
  *
@@ -47,7 +47,7 @@
  * \end{array} \right)
  * @f]
  *
- * After this operation, the output matrix will have the following shape: [ height * 4, ceil(width / 4.0f) ]
+ * After this operation, the output matrix will have the following shape: [ height * W, ceil(width / W) ] where W = 4 * mult_interleave4x4_height
  */
 class CLGEMMInterleave4x4Kernel : public ICLKernel
 {
@@ -64,18 +64,20 @@
     CLGEMMInterleave4x4Kernel &operator=(CLGEMMInterleave4x4Kernel &&) = default;
     /** Initialise the kernel's input and output.
      *
-     * @param[in]  input  Input tensor. Data types supported: U8/S8/QS8/QASYMM8/U16/S16/QS16/F16/U32/S32/F32
-     * @param[out] output Output tensor. Data type supported: same as @p input
+     * @param[in]  input                     Input tensor. Data types supported: U8/S8/QS8/QASYMM8/U16/S16/QS16/F16/U32/S32/F32
+     * @param[out] output                    Output tensor. Data type supported: same as @p input
+     * @param[in]  mult_interleave4x4_height (Optional) Multiplication factor for the height of the 4x4 interleave block
      */
-    void configure(const ICLTensor *input, ICLTensor *output);
+    void configure(const ICLTensor *input, ICLTensor *output, int mult_interleave4x4_height = 1);
     /** Static function to check if given info will lead to a valid configuration of @ref CLGEMMInterleave4x4Kernel
      *
-     * @param[in] input  Input tensor info. Data types supported: U8/S8/QS8/QASYMM8/U16/S16/QS16/F16/U32/S32/F32
-     * @param[in] output Output tensor info which stores the interleaved matrix. Data type supported: same as @p input.
+     * @param[in] input                     Input tensor info. Data types supported: U8/S8/QS8/QASYMM8/U16/S16/QS16/F16/U32/S32/F32
+     * @param[in] output                    Output tensor info which stores the interleaved matrix. Data type supported: same as @p input.
+     * @param[in] mult_interleave4x4_height Multiplication factor for the height of the 4x4 interleave block
      *
      * @return a status
      */
-    static Status validate(const ITensorInfo *input, const ITensorInfo *output);
+    static Status validate(const ITensorInfo *input, const ITensorInfo *output, int mult_interleave4x4_height);
 
     // Inherited methods overridden
     void run(const Window &window, cl::CommandQueue &queue) override;