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-rw-r--r--test/correctness/routines/levelx/xconvgemm.cpp24
-rw-r--r--test/correctness/testblas.hpp20
-rw-r--r--test/correctness/tester.cpp1
-rw-r--r--test/performance/client.cpp4
-rw-r--r--test/performance/routines/levelx/xconvgemm.cpp31
-rw-r--r--test/routines/levelx/xconvgemm.hpp243
6 files changed, 317 insertions, 6 deletions
diff --git a/test/correctness/routines/levelx/xconvgemm.cpp b/test/correctness/routines/levelx/xconvgemm.cpp
new file mode 100644
index 00000000..a120baa7
--- /dev/null
+++ b/test/correctness/routines/levelx/xconvgemm.cpp
@@ -0,0 +1,24 @@
+
+// =================================================================================================
+// This file is part of the CLBlast project. The project is licensed under Apache Version 2.0. This
+// project loosely follows the Google C++ styleguide and uses a tab-size of two spaces and a max-
+// width of 100 characters per line.
+//
+// Author(s):
+// Cedric Nugteren <www.cedricnugteren.nl>
+//
+// =================================================================================================
+
+#include "test/correctness/testblas.hpp"
+#include "test/routines/levelx/xconvgemm.hpp"
+
+// Main function (not within the clblast namespace)
+int main(int argc, char *argv[]) {
+ auto errors = size_t{0};
+ errors += clblast::RunTests<clblast::TestXconvgemm<float>, float, float>(argc, argv, false, "SCONVGEMM");
+ errors += clblast::RunTests<clblast::TestXconvgemm<double>, double, double>(argc, argv, true, "DCONVGEMM");
+ errors += clblast::RunTests<clblast::TestXconvgemm<clblast::half>, clblast::half, clblast::half>(argc, argv, true, "HCONVGEMM");
+ if (errors > 0) { return 1; } else { return 0; }
+}
+
+// =================================================================================================
diff --git a/test/correctness/testblas.hpp b/test/correctness/testblas.hpp
index 54b2d6f8..e9a995fd 100644
--- a/test/correctness/testblas.hpp
+++ b/test/correctness/testblas.hpp
@@ -60,6 +60,9 @@ class TestBlas: public Tester<T,U> {
static const std::vector<size_t> kDilationSizes;
static const std::vector<size_t> kKernelSizes;
static const std::vector<size_t> kBatchCounts;
+ static const std::vector<size_t> kNumKernels;
+ static const std::vector<size_t> kStrideValues;
+ static const std::vector<size_t> kChannelValues;
const std::vector<size_t> kOffsets;
const std::vector<U> kAlphaValues;
const std::vector<U> kBetaValues;
@@ -136,6 +139,9 @@ template <typename T, typename U> const std::vector<size_t> TestBlas<T,U>::kBatc
template <typename T, typename U> const std::vector<size_t> TestBlas<T,U>::kPadSizes = { 0, 1 };
template <typename T, typename U> const std::vector<size_t> TestBlas<T,U>::kDilationSizes = { 1, 2 };
template <typename T, typename U> const std::vector<size_t> TestBlas<T,U>::kKernelSizes = { 1, 3 };
+template <typename T, typename U> const std::vector<size_t> TestBlas<T,U>::kNumKernels = { 1, 6 };
+template <typename T, typename U> const std::vector<size_t> TestBlas<T,U>::kStrideValues = { 1, 3 };
+template <typename T, typename U> const std::vector<size_t> TestBlas<T,U>::kChannelValues = { 1, 2 };
// Test settings for the invalid tests
template <typename T, typename U> const std::vector<size_t> TestBlas<T,U>::kInvalidIncrements = { 0, 1 };
@@ -241,6 +247,7 @@ size_t RunTests(int argc, char *argv[], const bool silent, const std::string &na
auto dilation_hs = std::vector<size_t>{args.dilation_h};
auto dilation_ws = std::vector<size_t>{args.dilation_w};
auto batch_counts = std::vector<size_t>{args.batch_count};
+ auto num_kernelss = std::vector<size_t>{args.num_kernels};
auto x_sizes = std::vector<size_t>{args.x_size};
auto y_sizes = std::vector<size_t>{args.y_size};
auto a_sizes = std::vector<size_t>{args.a_size};
@@ -284,18 +291,19 @@ size_t RunTests(int argc, char *argv[], const bool silent, const std::string &na
if (option == kArgImaxOffset) { imax_offsets = tester.kOffsets; }
if (option == kArgAlpha) { alphas = tester.kAlphaValues; }
if (option == kArgBeta) { betas = tester.kBetaValues; }
- if (option == kArgChannels) { channelss = tester.kKernelSizes; }
+ if (option == kArgChannels) { channelss = tester.kChannelValues; }
if (option == kArgHeight) { heights = tester.kMatrixDims; }
if (option == kArgWidth) { widths = tester.kMatrixDims; }
if (option == kArgKernelH) { kernel_hs = tester.kKernelSizes; }
if (option == kArgKernelW) { kernel_ws = tester.kKernelSizes; }
if (option == kArgPadH) { pad_hs = tester.kPadSizes; }
if (option == kArgPadW) { pad_ws = tester.kPadSizes; }
- if (option == kArgStrideH) { stride_hs = tester.kKernelSizes; }
- if (option == kArgStrideW) { stride_ws = tester.kKernelSizes; }
+ if (option == kArgStrideH) { stride_hs = tester.kStrideValues; }
+ if (option == kArgStrideW) { stride_ws = tester.kStrideValues; }
if (option == kArgDilationH) { dilation_hs = tester.kDilationSizes; }
if (option == kArgDilationW) { dilation_ws = tester.kDilationSizes; }
if (option == kArgBatchCount) { batch_counts = tester.kBatchCounts; }
+ if (option == kArgNumKernels) { num_kernelss = tester.kNumKernels; }
if (option == kArgXOffset) { x_sizes = tester.kVecSizes; }
if (option == kArgYOffset) { y_sizes = tester.kVecSizes; }
@@ -350,8 +358,10 @@ size_t RunTests(int argc, char *argv[], const bool silent, const std::string &na
for (auto &dilation_h: dilation_hs) { r_args.dilation_h = dilation_h;
for (auto &dilation_w: dilation_ws) { r_args.dilation_w = dilation_w;
for (auto &batch_count: batch_counts) { r_args.batch_count = batch_count;
- C::SetSizes(r_args, tester.queue_);
- regular_test_vector.push_back(r_args);
+ for (auto &num_kernels: num_kernelss) { r_args.num_kernels = num_kernels;
+ C::SetSizes(r_args, tester.queue_);
+ regular_test_vector.push_back(r_args);
+ }
}
}
}
diff --git a/test/correctness/tester.cpp b/test/correctness/tester.cpp
index d6a346a6..daa43f26 100644
--- a/test/correctness/tester.cpp
+++ b/test/correctness/tester.cpp
@@ -370,6 +370,7 @@ std::string Tester<T,U>::GetOptionsString(const Arguments<U> &args) {
if (o == kArgChannels) { result += kArgChannels + equals + ToString(args.channels) + " "; }
if (o == kArgHeight) { result += kArgHeight + equals + ToString(args.height) + " "; }
if (o == kArgWidth) { result += kArgWidth + equals + ToString(args.width) + " "; }
+ if (o == kArgNumKernels){result += kArgNumKernels + equals + ToString(args.num_kernels) + " "; }
if (o == kArgKernelH) { result += kArgKernelH + equals + ToString(args.kernel_h) + " "; }
if (o == kArgKernelW) { result += kArgKernelW + equals + ToString(args.kernel_w) + " "; }
if (o == kArgPadH) { result += kArgPadH + equals + ToString(args.pad_h) + " "; }
diff --git a/test/performance/client.cpp b/test/performance/client.cpp
index e2d1a6c7..377e0140 100644
--- a/test/performance/client.cpp
+++ b/test/performance/client.cpp
@@ -106,7 +106,7 @@ Arguments<U> Client<T,U>::ParseArguments(int argc, char *argv[], const size_t le
if (o == kArgAlpha) { args.alpha = GetArgument(command_line_args, help, kArgAlpha, GetScalar<U>()); }
if (o == kArgBeta) { args.beta = GetArgument(command_line_args, help, kArgBeta, GetScalar<U>()); }
- // Arguments for im2col
+ // Arguments for im2col and convgemm
if (o == kArgChannels) { args.channels = GetArgument(command_line_args, help, kArgChannels, size_t{64}); }
if (o == kArgHeight) { args.height = GetArgument(command_line_args, help, kArgHeight, size_t{64}); }
if (o == kArgWidth) { args.width = GetArgument(command_line_args, help, kArgWidth, size_t{64}); }
@@ -118,6 +118,7 @@ Arguments<U> Client<T,U>::ParseArguments(int argc, char *argv[], const size_t le
if (o == kArgStrideW) { args.stride_w = GetArgument(command_line_args, help, kArgStrideW, size_t{1}); }
if (o == kArgDilationH) { args.dilation_h = GetArgument(command_line_args, help, kArgDilationH, size_t{1}); }
if (o == kArgDilationW) { args.dilation_w = GetArgument(command_line_args, help, kArgDilationW, size_t{1}); }
+ if (o == kArgNumKernels){ args.num_kernels = GetArgument(command_line_args, help, kArgNumKernels, size_t{1}); }
}
// These are the options common to all routines
@@ -446,6 +447,7 @@ void Client<T,U>::PrintTableRow(const Arguments<U>& args,
else if (o == kArgStrideW) {integers.push_back(args.stride_w); }
else if (o == kArgDilationH) {integers.push_back(args.dilation_h); }
else if (o == kArgDilationW) {integers.push_back(args.dilation_w); }
+ else if (o == kArgNumKernels){integers.push_back(args.num_kernels); }
}
auto strings = std::vector<std::string>{};
for (auto &o: options_) {
diff --git a/test/performance/routines/levelx/xconvgemm.cpp b/test/performance/routines/levelx/xconvgemm.cpp
new file mode 100644
index 00000000..2e255f8c
--- /dev/null
+++ b/test/performance/routines/levelx/xconvgemm.cpp
@@ -0,0 +1,31 @@
+
+// =================================================================================================
+// This file is part of the CLBlast project. The project is licensed under Apache Version 2.0. This
+// project loosely follows the Google C++ styleguide and uses a tab-size of two spaces and a max-
+// width of 100 characters per line.
+//
+// Author(s):
+// Cedric Nugteren <www.cedricnugteren.nl>
+//
+// =================================================================================================
+
+#include "test/performance/client.hpp"
+#include "test/routines/levelx/xconvgemm.hpp"
+
+// Main function (not within the clblast namespace)
+int main(int argc, char *argv[]) {
+ const auto command_line_args = clblast::RetrieveCommandLineArguments(argc, argv);
+ switch(clblast::GetPrecision(command_line_args, clblast::Precision::kSingle)) {
+ case clblast::Precision::kHalf:
+ clblast::RunClient<clblast::TestXconvgemm<clblast::half>, clblast::half, clblast::half>(argc, argv); break;
+ case clblast::Precision::kSingle:
+ clblast::RunClient<clblast::TestXconvgemm<float>, float, float>(argc, argv); break;
+ case clblast::Precision::kDouble:
+ clblast::RunClient<clblast::TestXconvgemm<double>, double, double>(argc, argv); break;
+ case clblast::Precision::kComplexSingle: throw std::runtime_error("Unsupported precision mode");
+ case clblast::Precision::kComplexDouble: throw std::runtime_error("Unsupported precision mode");
+ }
+ return 0;
+}
+
+// =================================================================================================
diff --git a/test/routines/levelx/xconvgemm.hpp b/test/routines/levelx/xconvgemm.hpp
new file mode 100644
index 00000000..7fa4e701
--- /dev/null
+++ b/test/routines/levelx/xconvgemm.hpp
@@ -0,0 +1,243 @@
+
+// =================================================================================================
+// This file is part of the CLBlast project. The project is licensed under Apache Version 2.0. This
+// project loosely follows the Google C++ styleguide and uses a tab-size of two spaces and a max-
+// width of 100 characters per line.
+//
+// Author(s):
+// Cedric Nugteren <www.cedricnugteren.nl>
+//
+// This file implements a class with static methods to describe the Xconvgemm routine. Examples of
+// such 'descriptions' are how to calculate the size a of buffer or how to run the routine. These
+// static methods are used by the correctness tester and the performance tester.
+//
+// =================================================================================================
+
+#ifndef CLBLAST_TEST_ROUTINES_XCONVGEMM_H_
+#define CLBLAST_TEST_ROUTINES_XCONVGEMM_H_
+
+#include "test/routines/common.hpp"
+
+namespace clblast {
+// =================================================================================================
+
+// See comment at top of file for a description of the class
+template <typename T>
+class TestXconvgemm {
+public:
+
+ // The BLAS level: 4 for the extra routines
+ static size_t BLASLevel() { return 4; }
+
+ // The list of arguments relevant for this routine
+ static std::vector<std::string> GetOptions() {
+ return {kArgChannels, kArgHeight, kArgWidth, kArgKernelH, kArgKernelW, kArgPadH, kArgPadW,
+ kArgStrideH, kArgStrideW, kArgDilationH, kArgDilationW, kArgNumKernels, kArgBatchCount,
+ kArgAOffset, kArgBOffset, kArgCOffset};
+ }
+ static std::vector<std::string> BuffersIn() { return {kBufMatA, kBufMatB, kBufMatC}; }
+ static std::vector<std::string> BuffersOut() { return {kBufMatC}; }
+
+ // Describes how to obtain the sizes of the buffers
+ static size_t OutputHeight(const Arguments<T> &args) {
+ const auto size = args.height + 2 * args.pad_h;
+ const auto padding = args.dilation_h * (args.kernel_h - 1) + 1;
+ if (size >= padding) { return (size - padding) / args.stride_h + 1; }
+ return 1;
+ }
+ static size_t OutputWidth(const Arguments<T> &args) {
+ const auto size = args.width + 2 * args.pad_w;
+ const auto padding = args.dilation_w * (args.kernel_w - 1) + 1;
+ if (size >= padding) { return (size - padding) / args.stride_w + 1; }
+ return 1;
+ }
+ static size_t NumPatches(const Arguments<T> &args) {
+ return OutputHeight(args) * OutputWidth(args) * args.channels;
+ }
+ static size_t GetSizeA(const Arguments<T> &args) { // 4D: NCHW == batch-channel-height-width
+ return args.batch_count * args.channels * args.height * args.width + args.a_offset;
+ }
+ static size_t GetSizeB(const Arguments<T> &args) { // 4D: KCHW == kernel-channel-height-width
+ return args.num_kernels * args.channels * args.kernel_h * args.kernel_w + args.b_offset;
+ }
+ static size_t GetSizeC(const Arguments<T> &args) { // 4D: NCHW == batch-channel-height-width
+ return args.batch_count * args.num_kernels * OutputHeight(args) * OutputWidth(args) + args.c_offset;
+ }
+
+ // Describes how to set the sizes of all the buffers
+ static void SetSizes(Arguments<T> &args, Queue&) {
+ args.a_size = GetSizeA(args);
+ args.b_size = GetSizeB(args);
+ args.c_size = GetSizeC(args);
+ }
+
+ // Describes what the default values of the leading dimensions of the matrices are
+ static size_t DefaultLDA(const Arguments<T> &) { return 1; } // N/A for this routine
+ static size_t DefaultLDB(const Arguments<T> &) { return 1; } // N/A for this routine
+ static size_t DefaultLDC(const Arguments<T> &) { return 1; } // N/A for this routine
+
+ // Describes which transpose options are relevant for this routine
+ using Transposes = std::vector<Transpose>;
+ static Transposes GetATransposes(const Transposes &) { return {}; } // N/A for this routine
+ static Transposes GetBTransposes(const Transposes &) { return {}; } // N/A for this routine
+
+ // Describes how to prepare the input data
+ static void PrepareData(const Arguments<T>&, Queue&, const int, std::vector<T>&,
+ std::vector<T>&, std::vector<T>&, std::vector<T>&, std::vector<T>&,
+ std::vector<T>&, std::vector<T>&) {} // N/A for this routine
+
+ // Describes how to run the CLBlast routine
+ static StatusCode RunRoutine(const Arguments<T> &args, Buffers<T> &buffers, Queue &queue) {
+#ifdef OPENCL_API
+ auto queue_plain = queue();
+ auto event = cl_event{};
+ auto status = Convgemm<T>(args.channels, args.height, args.width,
+ args.kernel_h, args.kernel_w,
+ args.pad_h, args.pad_w,
+ args.stride_h, args.stride_w,
+ args.dilation_h, args.dilation_w,
+ args.num_kernels, args.batch_count,
+ buffers.a_mat(), args.a_offset,
+ buffers.b_mat(), args.b_offset,
+ buffers.c_mat(), args.c_offset,
+ &queue_plain, &event);
+ if (status == StatusCode::kSuccess) { clWaitForEvents(1, &event); clReleaseEvent(event); }
+#elif CUDA_API
+ auto status = Convgemm<T>(args.channels, args.height, args.width,
+ args.kernel_h, args.kernel_w,
+ args.pad_h, args.pad_w,
+ args.stride_h, args.stride_w,
+ args.dilation_h, args.dilation_w,
+ args.num_kernels, args.batch_count,
+ buffers.a_mat(), args.a_offset,
+ buffers.b_mat(), args.b_offset,
+ buffers.c_mat(), args.c_offset,
+ queue.GetContext()(), queue.GetDevice()());
+ cuStreamSynchronize(queue());
+#endif
+ return status;
+ }
+
+ // Describes how to run a naive version of the routine (for correctness/performance comparison).
+ // Note that a proper clBLAS or CPU BLAS comparison is not available for non-BLAS routines.
+ static StatusCode RunReference1(const Arguments<T> &args, Buffers<T> &buffers, Queue &queue) {
+ auto buffers_host = BuffersHost<T>();
+ DeviceToHost(args, buffers, buffers_host, queue, BuffersIn());
+ const auto status = RunReference(args, buffers_host);
+ HostToDevice(args, buffers, buffers_host, queue, BuffersOut());
+ return status;
+ }
+
+ static StatusCode RunReference2(const Arguments<T> &args, BuffersHost<T> &buffers_host, Queue&) {
+ return RunReference(args, buffers_host);
+ }
+ static StatusCode RunReference3(const Arguments<T> &, BuffersCUDA<T> &, Queue &) {
+ return StatusCode::kUnknownError;
+ }
+
+ // Describes how to download the results of the computation (more importantly: which buffer)
+ static std::vector<T> DownloadResult(const Arguments<T> &args, Buffers<T> &buffers, Queue &queue) {
+ std::vector<T> result(args.c_size, static_cast<T>(0));
+ buffers.c_mat.Read(queue, args.c_size, result);
+ return result;
+ }
+
+ // Describes how to compute the indices of the result buffer
+ static size_t ResultID1(const Arguments<T> &args) { return OutputHeight(args) * OutputWidth(args); }
+ static size_t ResultID2(const Arguments<T> &args) { return args.num_kernels * args.batch_count; }
+ static size_t GetResultIndex(const Arguments<T> &args, const size_t id1, const size_t id2) {
+ return id1 + OutputHeight(args) * OutputWidth(args) * id2 + args.c_offset;
+ }
+
+ // Describes how to compute performance metrics
+ static size_t GetFlops(const Arguments<T> &args) {
+ const auto patch_size = args.kernel_h * args.kernel_w * args.channels;
+ const auto num_patches = OutputHeight(args) * OutputWidth(args);
+ return args.batch_count * 2 * num_patches * args.num_kernels * patch_size;
+ }
+ static size_t GetBytes(const Arguments<T> &args) {
+ return (GetSizeA(args) + GetSizeB(args) + GetSizeC(args)) * sizeof(T);
+ }
+};
+
+// =================================================================================================
+
+template <typename T>
+StatusCode RunReference(const Arguments<T> &args, BuffersHost<T> &buffers_host) {
+ const auto output_h = TestXconvgemm<T>::OutputHeight(args);
+ const auto output_w = TestXconvgemm<T>::OutputWidth(args);
+ for (auto batch_id = size_t{0}; batch_id < args.batch_count; ++batch_id) {
+ for (auto co_id = size_t{0}; co_id < args.num_kernels; ++co_id) { // output channels == num-kernels
+ for (auto ho_id = size_t{0}; ho_id < output_h; ++ho_id) { // image height
+ for (auto wo_id = size_t{0}; wo_id < output_w; ++wo_id) { // image width
+ auto result = ConstantZero<T>();
+
+ // 3D convolution
+ for (auto ci_id = size_t{0}; ci_id < args.channels; ++ci_id) { // input channels
+ for (auto kh_id = size_t{0}; kh_id < args.kernel_h; ++kh_id) { // kernel height
+ for (auto kw_id = size_t{0}; kw_id < args.kernel_w; ++kw_id) { // kernel width
+
+ // Retrieves the value from the input image
+ const auto hi_id = kh_id * args.dilation_h + args.stride_h * ho_id - args.pad_h;
+ const auto wi_id = kw_id * args.dilation_w + args.stride_w * wo_id - args.pad_w;
+ if (hi_id >= 0 && hi_id < args.height &&
+ wi_id >= 0 && wi_id < args.width) {
+ const auto input_index = wi_id + args.width * (
+ hi_id + args.height * (
+ ci_id + args.channels * (
+ batch_id)));
+ const auto input_value = buffers_host.a_mat[input_index + args.a_offset];
+
+ // Multiplies with the kernel tensor
+ const auto kernel_index = kw_id + args.kernel_w * (
+ kh_id + args.kernel_h * (
+ ci_id + args.channels * (
+ co_id)));
+ const auto kernel_value = buffers_host.b_mat[kernel_index + args.b_offset];
+ result += input_value * kernel_value;
+
+ }
+ }
+ }
+ }
+
+ // Sets the output value (NCHW == batch-channel-height-width)
+ const auto output_index = wo_id + output_w * (
+ ho_id + output_h * (
+ co_id + args.num_kernels * (
+ batch_id)));
+ buffers_host.c_mat[output_index + args.c_offset] = result;
+ }
+ }
+ }
+ }
+ return StatusCode::kSuccess;
+}
+
+// Half-precision version calling the above reference implementation after conversions
+template <>
+StatusCode RunReference<half>(const Arguments<half> &args, BuffersHost<half> &buffers_host) {
+ auto a_buffer2 = HalfToFloatBuffer(buffers_host.a_mat);
+ auto b_buffer2 = HalfToFloatBuffer(buffers_host.b_mat);
+ auto c_buffer2 = HalfToFloatBuffer(buffers_host.c_mat);
+ auto dummy = std::vector<float>(0);
+ auto buffers2 = BuffersHost<float>{dummy, dummy, a_buffer2, b_buffer2, c_buffer2, dummy, dummy};
+ auto args2 = Arguments<float>();
+ args2.a_size = args.a_size; args2.b_size = args.b_size; args2.c_size = args.c_size;
+ args2.channels = args.channels; args2.height = args.height; args2.width = args.width;
+ args2.kernel_h = args.kernel_h; args2.kernel_w = args.kernel_w;
+ args2.pad_h = args.pad_h; args2.pad_w = args.pad_w;
+ args2.stride_h = args.stride_h; args2.stride_w = args.stride_w;
+ args2.dilation_h = args.dilation_h; args2.dilation_w = args.dilation_w;
+ args2.num_kernels = args.num_kernels; args2.batch_count = args.batch_count;
+ args2.a_offset = args.a_offset; args2.b_offset = args.b_offset; args2.c_offset = args.c_offset;
+ auto status = RunReference(args2, buffers2);
+ FloatToHalfBuffer(buffers_host.c_mat, buffers2.c_mat);
+ return status;
+}
+
+// =================================================================================================
+} // namespace clblast
+
+// CLBLAST_TEST_ROUTINES_XCONVGEMM_H_
+#endif
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