Improve Winograd performance on OpenCL

- Performs more output elements per work-item in the case of Fp16
computation in Winograd Input/Output transform

Resolves COMPMID-6018

Signed-off-by: Gian Marco Iodice <gianmarco.iodice@arm.com>
Change-Id: If5e6f5182eff8c1f05a3505c437d0a997490f0bd
Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/9447
Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>
Tested-by: Arm Jenkins <bsgcomp@arm.com>
Reviewed-by: Jakub Sujak <jakub.sujak@arm.com>
Reviewed-by: Viet-Hoa Do <viet-hoa.do@arm.com>
Benchmark: Arm Jenkins <bsgcomp@arm.com>

2 files changed, 54 insertions, 13 deletions

diff --git a/src/gpu/cl/kernels/ClWinogradInputTransformKernel.cpp b/src/gpu/cl/kernels/ClWinogradInputTransformKernel.cpp
index d6b038f0f8..48d806dc7c 100644
--- a/src/gpu/cl/kernels/ClWinogradInputTransformKernel.cpp
+++ b/src/gpu/cl/kernels/ClWinogradInputTransformKernel.cpp
@@ -1,5 +1,5 @@
 /*
- * Copyright (c) 2018-2022 Arm Limited.
+ * Copyright (c) 2018-2023 Arm Limited.
  *
  * SPDX-License-Identifier: MIT
  *
@@ -79,8 +79,30 @@ std::pair<Status, Window> validate_and_configure_window(ITensorInfo *input, ITen
     ARM_COMPUTE_UNUSED(output);
     ARM_COMPUTE_ERROR_ON_NULLPTR(input, output);
 
-    bool   window_changed = false;
-    Window win            = calculate_max_window(*input, Steps(1, 1));
+    bool window_changed                    = false;
+    int  num_elems_processed_per_iteration = 1;
+
+    if(input->data_layout() == DataLayout::NHWC)
+    {
+        // In the case of FP16 computation, we can perform more
+        // output feature maps in a single work-item.
+        // From experiments, num_elems_processed_per_iteration = 2 looks good for fp16 to
+        // improve the performance. However, in order to make the implementation simpler,
+        // we set num_elems_processed_per_iteration = 2 only when the OFMs are multiple of 2.
+        // Note: At the moment, only Winograd Input Transform 3x3 can support N0 != 1
+        const DataType dt   = input->data_type();
+        const size_t   dim0 = input->dimension(0);
+        const size_t   k_sz = winograd_info.kernel_size.area();
+        const bool     cond = dt == DataType::F16 && ((dim0 % 2) == 0);
+        if(cond)
+        {
+            if(k_sz == 3 || k_sz == 9)
+            {
+                num_elems_processed_per_iteration = 2;
+            }
+        }
+    }
+    Window win = calculate_max_window(*input, Steps(num_elems_processed_per_iteration));
 
     if(input->data_layout() == DataLayout::NCHW)
     {
@@ -143,12 +165,19 @@ void ClWinogradInputTransformKernel::configure(const ClCompileContext &compile_c
     ARM_COMPUTE_ERROR_ON(_num_tiles_x * _num_tiles_y != static_cast<int>(dst->dimension(1)));
     const size_t total_batches = src->tensor_shape().total_size_upper(3);
 
+    // Create window and update padding
+    auto win_config = validate_and_configure_window(src, dst, winograd_info);
+    ARM_COMPUTE_ERROR_THROW_ON(win_config.first);
+    IClKernel::configure_internal(win_config.second, cl::NDRange(1, 1, 8));
+
+    _src_width  = src->dimension(idx_w);
+    _src_height = src->dimension(idx_h);
+
     CLBuildOptions build_opts;
     if(_data_layout == DataLayout::NHWC)
     {
         build_opts.add_option("-DNHWC");
-        _src_width  = src->dimension(idx_w);
-        _src_height = src->dimension(idx_h);
+        build_opts.add_option("-DN0=" + support::cpp11::to_string(win_config.second.x().step()));
         build_opts.add_option("-DPAD_LEFT=" + support::cpp11::to_string(conv_info.pad_left()));
         build_opts.add_option("-DPAD_TOP=" + support::cpp11::to_string(conv_info.pad_top()));
         build_opts.add_option("-DOUTPUT_TILE_W=" + support::cpp11::to_string(output_tile_size.width));
@@ -156,6 +185,7 @@ void ClWinogradInputTransformKernel::configure(const ClCompileContext &compile_c
         build_opts.add_option("-DDATA_TYPE=" + get_cl_type_from_data_type(src->data_type()));
         build_opts.add_option_if(winograd_info.kernel_size.height == 1, "-DWINOGRAD_INPUT_TRANSFORM_HORIZONTAL");
         build_opts.add_option_if(winograd_info.kernel_size.width == 1, "-DWINOGRAD_INPUT_TRANSFORM_VERTICAL");
+        build_opts.add_option_if(total_batches > 1, "-DIS_BATCHED");
     }
     else
     {
@@ -191,11 +221,6 @@ void ClWinogradInputTransformKernel::configure(const ClCompileContext &compile_c
     build_opts.add_option("-D" + upper_string(kernel_name));
     _kernel = create_kernel(compile_context, kernel_name, build_opts.options());
 
-    // Create window and update padding
-    auto win_config = validate_and_configure_window(src, dst, winograd_info);
-    ARM_COMPUTE_ERROR_THROW_ON(win_config.first);
-    IClKernel::configure_internal(win_config.second, cl::NDRange(1, 1, 8));
-
     _border_size = BorderSize(src->padding());
 
     ARM_COMPUTE_ERROR_ON((src->data_layout() == DataLayout::NHWC) && has_padding_changed(padding_info));
diff --git a/src/gpu/cl/kernels/ClWinogradOutputTransformKernel.cpp b/src/gpu/cl/kernels/ClWinogradOutputTransformKernel.cpp
index 9eb249a66a..c5c24886bd 100644
--- a/src/gpu/cl/kernels/ClWinogradOutputTransformKernel.cpp
+++ b/src/gpu/cl/kernels/ClWinogradOutputTransformKernel.cpp
@@ -1,5 +1,5 @@
 /*
- * Copyright (c) 2018-2022 Arm Limited.
+ * Copyright (c) 2018-2023 Arm Limited.
  *
  * SPDX-License-Identifier: MIT
  *
@@ -102,7 +102,23 @@ std::pair<Status, Window> validate_and_configure_window(ITensorInfo *input, ITen
     ARM_COMPUTE_ERROR_ON_NULLPTR(input, output);
     ARM_COMPUTE_UNUSED(bias);
 
-    constexpr unsigned int num_elems_processed_per_iteration = 1;
+    unsigned int num_elems_processed_per_iteration = 1;
+
+    if(input->data_layout() == DataLayout::NHWC)
+    {
+        // In the case of FP16 computation, we can perform more
+        // output feature maps in a single work-item.
+        // From experiments, num_elems_processed_per_iteration = 2 looks good for fp16 to
+        // improve the performance. However, in order to make the implementation simpler,
+        // we set num_elems_processed_per_iteration = 2 only when the OFMs are multiple of 2.
+        const DataType dt   = input->data_type();
+        const size_t   dim0 = input->dimension(0);
+        const bool     cond = dt == DataType::F16 && ((dim0 % 2) == 0);
+        if(cond)
+        {
+            num_elems_processed_per_iteration = 2;
+        }
+    }
 
     Window win            = calculate_max_window(*input, Steps(num_elems_processed_per_iteration));
     bool   window_changed = false;
@@ -203,7 +219,7 @@ void ClWinogradOutputTransformKernel::configure(const ClCompileContext &compile_
         build_opts.add_option("-DOUTPUT_TILE_W=" + support::cpp11::to_string(output_tile_size.width));
         build_opts.add_option("-DOUTPUT_TILE_H=" + support::cpp11::to_string(output_tile_size.height));
         build_opts.add_option("-DDATA_TYPE=" + get_cl_type_from_data_type(src_data_type));
-        build_opts.add_option_if(total_batches > 1, "-DSRC_DEPTH=" + support::cpp11::to_string(src->dimension(2)));
+        build_opts.add_option_if(total_batches > 1, "-DIS_BATCHED");
         build_opts.add_option_if(winograd_info.kernel_size.height == 1, "-DWINOGRAD_OUTPUT_TRANSFORM_HORIZONTAL");
         build_opts.add_option_if(winograd_info.kernel_size.width == 1, "-DWINOGRAD_OUTPUT_TRANSFORM_VERTICAL");
         build_opts.add_option("-DNUM_TILES_X=" + support::cpp11::to_string(_num_tiles_x));