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// =================================================================================================
// 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 tunes the Xgemm routine at a high-level: choosing between the direct (single-kernel)
// and the in-direct (kernel plus pre/post-processing) methods.
//
// =================================================================================================
#include <exception>
#include <string>
#include <vector>
#include "utilities/utilities.hpp"
#include "tuning/routines/routine_tuner.hpp"
namespace clblast {
// =================================================================================================
template <typename T>
void RunGemmRoutine(const size_t value, const Queue& queue, const std::vector<Buffer<T>>& buffers) {
auto queue_plain = queue();
auto event = cl_event{};
auto status = Gemm(Layout::kRowMajor, Transpose::kNo, Transpose::kNo,
value, value, value, ConstantOne<T>(),
buffers[0](), 0, value,
buffers[1](), 0, value, ConstantOne<T>(),
buffers[2](), 0, value,
&queue_plain, &event);
if (status != StatusCode::kSuccess) {
throw RuntimeError("Gemm failed with status " + ToString(status));
}
clWaitForEvents(1, &event);
clReleaseEvent(event);
}
template <typename T, size_t batch_count>
void RunGemmBatchedRoutine(const size_t value, const Queue& queue, const std::vector<Buffer<T>>& buffers) {
auto offsets = std::vector<size_t>(batch_count);
auto factors = std::vector<T>(batch_count);
for (auto i = size_t{0}; i < batch_count; ++i) {
offsets[i] = batch_count * value;
factors[i] = ConstantOne<T>();
}
auto queue_plain = queue();
auto event = cl_event{};
auto status = GemmBatched(Layout::kRowMajor, Transpose::kNo, Transpose::kNo,
value, value, value, factors.data(),
buffers[0](), offsets.data(), value,
buffers[1](), offsets.data(), value, factors.data(),
buffers[2](), offsets.data(), value, batch_count,
&queue_plain, &event);
if (status != StatusCode::kSuccess) {
throw RuntimeError("GemmBatched failed with status " + ToString(status));
}
clWaitForEvents(1, &event);
clReleaseEvent(event);
}
template <typename T, size_t batch_count>
void RunGemmStridedBatchedRoutine(const size_t value, const Queue& queue, const std::vector<Buffer<T>>& buffers) {
auto queue_plain = queue();
auto event = cl_event{};
auto status = GemmStridedBatched(Layout::kRowMajor, Transpose::kNo, Transpose::kNo,
value, value, value, ConstantOne<T>(),
buffers[0](), 0, value, value * value,
buffers[1](), 0, value, value * value, ConstantOne<T>(),
buffers[2](), 0, value, value * value, batch_count,
&queue_plain, &event);
if (status != StatusCode::kSuccess) {
throw RuntimeError("Gemm failed with status " + ToString(status));
}
clWaitForEvents(1, &event);
clReleaseEvent(event);
}
// =================================================================================================
template <typename T>
void TuneXgemm(int argc, char* argv[]) {
auto command_line_args = RetrieveCommandLineArguments(argc, argv);
auto help = std::string{"* Options given/available:\n"};
const auto platform_id = GetArgument(command_line_args, help, kArgPlatform, ConvertArgument(std::getenv("CLBLAST_PLATFORM"), size_t{0}));
const auto device_id = GetArgument(command_line_args, help, kArgDevice, ConvertArgument(std::getenv("CLBLAST_DEVICE"), size_t{0}));
const auto precision = GetArgument(command_line_args, help, kArgPrecision, Precision::kSingle);
const auto num_runs = GetArgument(command_line_args, help, kArgNumRuns, size_t{10});
fprintf(stdout, "%s\n", help.c_str());
// OpenCL initialisation
const auto platform = Platform(platform_id);
const auto device = Device(platform, device_id);
if (!PrecisionSupported<T>(device)) {
printf("* Unsupported precision, skipping this tuning run\n");
return;
}
const auto context = Context(device);
auto queue = Queue(context, device);
// Run the tuners for the XGEMM routines
TuneKernelSelection<T>(platform, device, context, queue, precision, RunGemmRoutine<T>,
64, 2048, 64, 1, num_runs,
"gemm", "GemmRoutine", "gemm_routine", "XGEMM_MIN_INDIRECT_SIZE");
//TuneKernelSelection<T>(platform, device, context, queue, precision, RunGemmBatchedRoutine<T, 30>,
// 16, 128, 32, 30, num_runs,
// "gemmbatched", "GemmRoutine", "gemm_routine_2", "XGEMMBATCHED_MIN_INDIRECT_SIZE");
//TuneKernelSelection<T>(platform, device, context, queue, precision, RunGemmStridedBatchedRoutine<T, 30>,
// 16, 128, 32, 30, num_runs,
// "gemmstridedbatched", "GemmRoutine", "gemm_routine_3", "XGEMMSTRIDEDBATCHED_MIN_INDIRECT_SIZE");
printf("* Completed tuning process\n");
printf("\n");
}
// =================================================================================================
} // namespace clblast
// Shortcuts to the clblast namespace
using half = clblast::half;
using float2 = clblast::float2;
using double2 = clblast::double2;
// 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)) {
case clblast::Precision::kHalf: clblast::TuneXgemm<half>(argc, argv); break;
case clblast::Precision::kSingle: clblast::TuneXgemm<float>(argc, argv); break;
case clblast::Precision::kDouble: clblast::TuneXgemm<double>(argc, argv); break;
case clblast::Precision::kComplexSingle: clblast::TuneXgemm<float2>(argc, argv); break;
case clblast::Precision::kComplexDouble: clblast::TuneXgemm<double2>(argc, argv); break;
}
return 0;
}
// =================================================================================================
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