Added method selection option to switch between im2col and single-kernel approach for convgemm

1 files changed, 60 insertions, 45 deletions

diff --git a/src/routines/levelx/xconvgemm.cpp b/src/routines/levelx/xconvgemm.cpp
index 055a3dda..5ad39751 100644
--- a/src/routines/levelx/xconvgemm.cpp
+++ b/src/routines/levelx/xconvgemm.cpp
@@ -22,9 +22,11 @@ namespace clblast {
 
 // Constructor: forwards to base class constructor
 template <typename T>
-Xconvgemm<T>::Xconvgemm(Queue &queue, EventPointer event, const std::string &name):
+Xconvgemm<T>::Xconvgemm(Queue &queue, EventPointer event, const std::string &name,
+                        const ConvGemmMethod method):
     Routine(queue, event, name, {"XgemmDirect"},
         PrecisionValue<T>(), {}, {
+            (method == ConvGemmMethod::kWithIm2Col) ? "#define CONVGEMM_WITH_IM2COL\n" : "",
             #include "../../kernels/level3/level3.opencl"
             , // separated in multiple parts to prevent C1091 in MSVC 2013
             #include "../../kernels/level3/xgemm_direct_part1.opencl"
@@ -33,7 +35,8 @@ Xconvgemm<T>::Xconvgemm(Queue &queue, EventPointer event, const std::string &nam
             , // separated in multiple parts to prevent C1091 in MSVC 2013
             #include "../../kernels/levelx/xconvgemm_part1.opencl"
             #include "../../kernels/levelx/xconvgemm_part2.opencl"
-        }) {
+        }),
+    method_(method) {
 }
 
 // =================================================================================================
@@ -70,26 +73,29 @@ void Xconvgemm<T>::DoConvgemm(const size_t channels, const size_t height, const
   const auto patch_size = kernel_h * kernel_w * channels;
   const auto num_patches = output_h * output_w;
 
-  // Approach: im2col + GEMM
+  // Possible approach: im2col + GEMM
   //      result = GEMM(im2col(image), kernel)
-
-  // Temporary col matrix
-  const auto col_size = patch_size * num_patches * batch_count;
-  auto col_buffer = Buffer<T>(context_, col_size);
-
-  // Loops over each batch
-  for (auto batch_id = size_t{0}; batch_id < batch_count; ++batch_id) {
-
-    // im2col
-    const auto im_batch_offset = batch_id * channels * height * width + im_offset;
-    const auto col_batch_offset = batch_id * patch_size * num_patches;
-    auto im2col_event = Event();
-    auto im2col = Xim2col<T>(queue_, im2col_event.pointer());
-    im2col.DoIm2col(channels, height, width, kernel_h, kernel_w,
-                    pad_h, pad_w, stride_h, stride_w, dilation_h, dilation_w,
-                    im_buffer, im_batch_offset,
-                    col_buffer, col_batch_offset);
-    im2col_event.WaitForCompletion();
+  auto col_buffer = Buffer<T>(context_, 0); // nullptr, will be optionally created later
+  if (method_ == ConvGemmMethod::kWithIm2Col) {
+
+    // Temporary col matrix
+    const auto col_size = (method_ == ConvGemmMethod::kWithIm2Col) ? patch_size * num_patches * batch_count : 1;
+    col_buffer = Buffer<T>(context_, col_size);
+
+    // Loops over each batch
+    for (auto batch_id = size_t{0}; batch_id < batch_count; ++batch_id) {
+
+      // im2col
+      const auto im_batch_offset = batch_id * channels * height * width + im_offset;
+      const auto col_batch_offset = batch_id * patch_size * num_patches;
+      auto im2col_event = Event();
+      auto im2col = Xim2col<T>(queue_, im2col_event.pointer());
+      im2col.DoIm2col(channels, height, width, kernel_h, kernel_w,
+                      pad_h, pad_w, stride_h, stride_w, dilation_h, dilation_w,
+                      im_buffer, im_batch_offset,
+                      col_buffer, col_batch_offset);
+      im2col_event.WaitForCompletion();
+    }
   }
 
   // Strided batched GEMM: C (result) = alpha (1) * A (col) * B (kernel) + beta (0) * C (result)
@@ -99,7 +105,12 @@ void Xconvgemm<T>::DoConvgemm(const size_t channels, const size_t height, const
   // Tests the matrices for validity
   TestMatrixB(patch_size, num_kernels, kernel_buffer, kernel_offset, patch_size);
   for (auto batch = size_t{0}; batch < batch_count; ++batch) {
-    TestMatrixA(num_patches, patch_size, col_buffer, col_stride * batch, num_patches);
+    if (method_ == ConvGemmMethod::kWithIm2Col) {
+      TestMatrixA(num_patches, patch_size, col_buffer, col_stride * batch, num_patches);
+    }
+    else {
+      // TODO: check for valid image tensor
+    }
     TestMatrixC(num_patches, num_kernels, result_buffer, result_offset + result_stride * batch, num_patches);
   }
 
@@ -110,29 +121,33 @@ void Xconvgemm<T>::DoConvgemm(const size_t channels, const size_t height, const
   kernel.SetArgument(0, static_cast<int>(num_patches));
   kernel.SetArgument(1, static_cast<int>(num_kernels));
   kernel.SetArgument(2, static_cast<int>(patch_size));
-  kernel.SetArgument(3, col_buffer());
-  kernel.SetArgument(4, static_cast<int>(0));
-  kernel.SetArgument(5, static_cast<int>(col_stride));
-  kernel.SetArgument(6, kernel_buffer());
-  kernel.SetArgument(7, static_cast<int>(kernel_offset));
-  kernel.SetArgument(8, result_buffer());
-  kernel.SetArgument(9, static_cast<int>(result_offset));
-  kernel.SetArgument(10, static_cast<int>(result_stride));
-  kernel.SetArgument(11, static_cast<int>(height));
-  kernel.SetArgument(12, static_cast<int>(width));
-  kernel.SetArgument(13, static_cast<int>(channels));
-  kernel.SetArgument(14, static_cast<int>(kernel_h));
-  kernel.SetArgument(15, static_cast<int>(kernel_w));
-  kernel.SetArgument(16, static_cast<int>(pad_h));
-  kernel.SetArgument(17, static_cast<int>(pad_w));
-  kernel.SetArgument(18, static_cast<int>(stride_h));
-  kernel.SetArgument(19, static_cast<int>(stride_w));
-  kernel.SetArgument(20, static_cast<int>(dilation_h));
-  kernel.SetArgument(21, static_cast<int>(dilation_w));
-  kernel.SetArgument(22, im_buffer());
-  kernel.SetArgument(23, static_cast<int>(im_offset));
-  kernel.SetArgument(24, static_cast<int>(output_h));
-  kernel.SetArgument(25, static_cast<int>(output_w));
+  kernel.SetArgument(3, kernel_buffer());
+  kernel.SetArgument(4, static_cast<int>(kernel_offset));
+  kernel.SetArgument(5, result_buffer());
+  kernel.SetArgument(6, static_cast<int>(result_offset));
+  kernel.SetArgument(7, static_cast<int>(result_stride));
+  if (method_ == ConvGemmMethod::kWithIm2Col) {
+    kernel.SetArgument(8, col_buffer());
+    kernel.SetArgument(9, static_cast<int>(0));
+    kernel.SetArgument(10, static_cast<int>(col_stride));
+  }
+  if (method_ == ConvGemmMethod::kSingleKernel) {
+    kernel.SetArgument(8, im_buffer());
+    kernel.SetArgument(9, static_cast<int>(im_offset));
+    kernel.SetArgument(10, static_cast<int>(height));
+    kernel.SetArgument(11, static_cast<int>(width));
+    kernel.SetArgument(12, static_cast<int>(channels));
+    kernel.SetArgument(13, static_cast<int>(kernel_h));
+    kernel.SetArgument(14, static_cast<int>(kernel_w));
+    kernel.SetArgument(15, static_cast<int>(pad_h));
+    kernel.SetArgument(16, static_cast<int>(pad_w));
+    kernel.SetArgument(17, static_cast<int>(stride_h));
+    kernel.SetArgument(18, static_cast<int>(stride_w));
+    kernel.SetArgument(19, static_cast<int>(dilation_h));
+    kernel.SetArgument(20, static_cast<int>(dilation_w));
+    kernel.SetArgument(21, static_cast<int>(output_h));
+    kernel.SetArgument(22, static_cast<int>(output_w));
+  }
 
   // Computes the global and local thread sizes
   const auto m_ceiled = Ceil(num_patches, db_["WGD"]);