CUBLAS benchmark

CMakeLists.txt

cmake_minimum_required(VERSION 3.18)

set(PROJECT_NAME BMcublas)
project(${PROJECT_NAME})

include(CheckLanguage)
check_language(CUDA CXX)
enable_language(CUDA CXX)

# Set C++ standard
set(CMAKE_BUILD_WITH_INSTALL_RPATH TRUE)
set(CMAKE_CXX_STANDARD 17)
set(CMAKE_CXX_STANDARD_REQUIRED ON)

find_package(benchmark REQUIRED)
find_package(CUDA 11.0 REQUIRED)

add_executable(${PROJECT_NAME} main.cpp)
target_include_directories(${PROJECT_NAME} PUBLIC SYSTEM ${CUDA_INCLUDE_DIRS})
target_link_libraries(${PROJECT_NAME} ${CUDA_LIBRARIES} ${CUDA_CUBLAS_LIBRARIES} benchmark::benchmark)

main.cpp

#include "src.hpp"
#include <benchmark/benchmark.h>
#include <chrono>

double value = 1. / 3.;

using namespace std::chrono;

template <typename T>
static void BM_copy(benchmark::State& state) {
  std::size_t n = state.range(0);

  cublasHandle_t handle;
  cublasCreate(&handle);

  cudaEvent_t start, stop;
  cudaEventCreate(&start);
  cudaEventCreate(&stop);

  T* x = kernel::init_vector<T>(handle, n, value);
  T* y = kernel::init_vector<T>(handle, n, -value);

  for (auto _ : state) {
    cudaEventRecord(start);
    kernel::copy<T>(handle, n, x, y);
    cudaEventRecord(stop);
    cudaEventSynchronize(stop);
    float t = 0;
    cudaEventElapsedTime(&t, start, stop);
    state.SetIterationTime(t / 1e3);
  }

  state.SetBytesProcessed(sizeof(T) * 2 * n * state.iterations());
  state.SetLabel("cublas");

  cublasDestroy(handle);
  cudaFree(&x);
  cudaFree(&y);
}

template <typename T>
static void BM_axpy(benchmark::State& state) {
  std::size_t n = state.range(0);
  cublasHandle_t handle;
  cublasCreate(&handle);

  T* x = kernel::init_vector<T>(handle, n, value);
  T* y = kernel::init_vector<T>(handle, n, -value);
  T alpha = 1.;

  cudaEvent_t start, stop;
  cudaEventCreate(&start);
  cudaEventCreate(&stop);

  for (auto _ : state) {
    cudaEventRecord(start);
    kernel::axpy<T>(handle, n, alpha, x, y);
    cudaEventRecord(stop);
    cudaEventSynchronize(stop);
    float t = 0;
    cudaEventElapsedTime(&t, start, stop);
    state.SetIterationTime(t / 1e3);
  }

  state.SetBytesProcessed(sizeof(T) * 2 * n * state.iterations());
  state.SetLabel("cublas");

  cublasDestroy(handle);
  cudaFree(&x);
  cudaFree(&y);
}

template <typename T>
static void BM_dot(benchmark::State& state) {
  std::size_t n = state.range(0);
  cublasHandle_t handle;
  cublasCreate(&handle);

  T* x = kernel::init_vector<T>(handle, n, value);
  T* y = kernel::init_vector<T>(handle, n, -value);

  cudaEvent_t start, stop;
  cudaEventCreate(&start);
  cudaEventCreate(&stop);

  for (auto _ : state) {
    cudaEventRecord(start);
    T result = kernel::dot<T>(handle, n, x, y);
    benchmark::DoNotOptimize(result);
    cudaEventRecord(stop);
    cudaEventSynchronize(stop);
    float t = 0;
    cudaEventElapsedTime(&t, start, stop);
    state.SetIterationTime(t / 1e3);
  }

  state.SetBytesProcessed(sizeof(T) * 2 * n * state.iterations());
  state.SetLabel("cublas");

  cublasDestroy(handle);
  cudaFree(&x);
  cudaFree(&y);
}

BENCHMARK_TEMPLATE(BM_copy, double)
    ->RangeMultiplier(2)
    ->Range(1 << 8, 1 << 29)
    ->UseManualTime();
BENCHMARK_TEMPLATE(BM_axpy, double)
    ->RangeMultiplier(2)
    ->Range(1 << 8, 1 << 29)
    ->UseManualTime();
BENCHMARK_TEMPLATE(BM_dot, double)
    ->RangeMultiplier(2)
    ->Range(1 << 8, 1 << 29)
    ->UseManualTime();

int main(int argc, char** argv) {
  kernel::print_device_info();
  ::benchmark::Initialize(&argc, argv);
  if (::benchmark::ReportUnrecognizedArguments(argc, argv))
    return 1;
  ::benchmark::RunSpecifiedBenchmarks();
}

src.hpp

#include <cuda_runtime.h>
#include <stdexcept>
#include <type_traits>

#include "cublas_v2.h"

template <class T>
struct unrecognized_type : std::false_type {};

namespace kernel {

void print_device_info() {
  int num_devices;

  cudaGetDeviceCount(&num_devices);
  for (int i = 0; i < num_devices; i++) {
    cudaDeviceProp prop;
    cudaGetDeviceProperties(&prop, i);
    double bandwidth = 2.0 * prop.memoryClockRate * (prop.memoryBusWidth / 8) / 1.0e6;
    std::cout << "Device Number: " << i << std::endl;
    std::cout << "\tDevice name: " << prop.name << std::endl;
    std::cout << "\tShared memory available per block (kB): "
              << prop.sharedMemPerBlock / 1e3 << std::endl;
    std::cout << "\tGlobal memory available (GB): " << prop.totalGlobalMem / 1e9
              << std::endl;
    std::cout << "\tPeak Memory Bandwidth (GB/s): " << bandwidth << std::endl;
  }
  std::cout << std::endl;
}

void assert_cuda(cudaError_t e) {
  if (e != cudaSuccess)
    throw std::runtime_error(" Unable to allocate memoy - cublas error");
}

template <typename T>
T* init_vector(cublasHandle_t handle, std::size_t n, T value) {
  T* x;
  assert_cuda(cudaMalloc(&x, n * sizeof(T)));
  assert_cuda(cudaMemset(x, value, n * sizeof(T)));
  return x;
}

template <typename T>
void copy(cublasHandle_t handle, std::size_t n, T* x, T* y) {
  if constexpr (std::is_same<T, double>())
    cublasDcopy(handle, n, x, 1, y, 1);
  else if constexpr (std::is_same<T, float>())
    cublasScopy(handle, n, x, 1, y, 1);
}

template <typename T>
void axpy(cublasHandle_t handle, std::size_t n, T alpha, T* x, T* y) {
  if constexpr (std::is_same<T, double>())
    cublasDaxpy(handle, n, &alpha, x, 1, y, 1);
  else if constexpr (std::is_same<T, float>())
    cublasSaxpy(handle, n, &alpha, x, 1, y, 1);
}

template <typename T>
T dot(cublasHandle_t handle, std::size_t n, T* x, T* y) {
  T result = 0;
  if constexpr (std::is_same<T, double>())
    cublasDdot(handle, n, x, 1, y, 1, &result);
  else if constexpr (std::is_same<T, float>())
    cublasSdot(handle, n, x, 1, y, 1, &result);

  return result;
}

} // namespace kernel

Make:

mkdir build
cd build
cmake ..
make

Run:

./BMcublas --benchmark_filter=copy
./BMcublas --benchmark_filter=axpy
./BMcublas --benchmark_filter=dot