Update the heuristic to call direct convolution in clConv2d

Resolves COMPMID-4773

Change-Id: Id0e4126bd28025d13011a14cba99022a1c88322a
Signed-off-by: Gian Marco Iodice <gianmarco.iodice@arm.com>
Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/6123
Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>
Tested-by: Arm Jenkins <bsgcomp@arm.com>
Reviewed-by: Pablo Marquez Tello <pablo.tello@arm.com>

1 files changed, 35 insertions, 5 deletions

diff --git a/src/runtime/gpu/cl/operators/ClConv2d.cpp b/src/runtime/gpu/cl/operators/ClConv2d.cpp
index 4cd65290f3..2f4d673d9c 100644
--- a/src/runtime/gpu/cl/operators/ClConv2d.cpp
+++ b/src/runtime/gpu/cl/operators/ClConv2d.cpp
@@ -36,6 +36,35 @@
 
 #include <memory>
 
+namespace
+{
+/** Get the suitable kernel size for using direct convolution method with NHWC data layout.
+ *
+ * @note Direct convolution should be executed when the kernel has the spatial dimensions greater than or equal to the value returned by this function
+ *
+ * @param[in] gpu_target GPU target
+ *
+ * @return the suitable kernel size for using direct convolution method with NHWC data layout
+ */
+size_t get_direct_conv_kernel_threshold_nhwc(arm_compute::GPUTarget gpu_target)
+{
+    switch(gpu_target)
+    {
+        case arm_compute::GPUTarget::G76:
+        case arm_compute::GPUTarget::G77:
+        case arm_compute::GPUTarget::G78:
+            return 5;
+        case arm_compute::GPUTarget::G71:
+        case arm_compute::GPUTarget::G72:
+        case arm_compute::GPUTarget::MIDGARD:
+        case arm_compute::GPUTarget::BIFROST:
+            return 7;
+        default:
+            return 5;
+    }
+}
+} // namespace
+
 namespace arm_compute
 {
 namespace opencl
@@ -132,7 +161,6 @@ ConvolutionMethod ClConv2d::get_convolution_method(const ITensorInfo *src, const
     ARM_COMPUTE_ERROR_ON_NULLPTR(dst);
     ARM_COMPUTE_ERROR_ON_NULLPTR(weights);
     ARM_COMPUTE_UNUSED(weights_info);
-    ARM_COMPUTE_UNUSED(gpu_target);
 
     const PadStrideInfo       conv_info        = conv2d_info.conv_info;
     const ActivationLayerInfo act_info         = conv2d_info.act_info;
@@ -206,8 +234,9 @@ ConvolutionMethod ClConv2d::get_convolution_method(const ITensorInfo *src, const
         }
         else
         {
-            const bool is_direct_valid = bool(ClDirectConv2d::validate(src, weights, nullptr, dst, conv_info, act_info));
-            const bool is_wino_valid   = bool(ClWinogradConv2d::validate(src, weights, nullptr, dst, conv_info, act_info, enable_fast_math));
+            const bool   is_direct_valid           = bool(ClDirectConv2d::validate(src, weights, nullptr, dst, conv_info, act_info));
+            const bool   is_wino_valid             = bool(ClWinogradConv2d::validate(src, weights, nullptr, dst, conv_info, act_info, enable_fast_math));
+            const size_t kernel_sz_direct_conv_thr = get_direct_conv_kernel_threshold_nhwc(gpu_target);
 
             // SRGAN case
             if((src->dimension(idx_h) > 720U) && (dst->dimension(idx_h) > 720U) && (weights->dimension(idx_h) == 9) && (conv_info.pad_top() < 3)
@@ -219,8 +248,9 @@ ConvolutionMethod ClConv2d::get_convolution_method(const ITensorInfo *src, const
             // Floating-point case: GeMM/Direct/Winograd
             if(is_data_type_float(src->data_type()))
             {
-                const bool is_large_kernel_sz = (weights->dimension(idx_w) >= 7) && (weights->dimension(idx_h) >= 7);
+                const bool is_large_kernel_sz = (weights->dimension(idx_w) >= kernel_sz_direct_conv_thr) && (weights->dimension(idx_h) >= kernel_sz_direct_conv_thr);
                 const bool is_ifm_ge_16       = src->dimension(idx_c) >= 16;
+                const bool is_ifm_gt_ofm      = src->dimension(idx_c) > weights->dimension(3U);
 
                 // Run Winograd if valid and IFM >= 16
                 if(is_wino_valid && is_ifm_ge_16)
@@ -228,7 +258,7 @@ ConvolutionMethod ClConv2d::get_convolution_method(const ITensorInfo *src, const
                     return ConvolutionMethod::WINOGRAD;
                 }
                 // Run Direct for Large kernel size
-                if(is_large_kernel_sz && is_ifm_ge_16 && is_direct_valid)
+                if(is_large_kernel_sz && is_ifm_ge_16 && is_direct_valid && is_ifm_gt_ofm)
                 {
                     return ConvolutionMethod::DIRECT;
                 }