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basic GEMM version

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PatricZhao 2年前
committed by GitHub
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この署名に対応する既知のキーがデータベースに存在しません GPGキーID: 4AEE18F83AFDEB23
1個のファイルの変更157行の追加0行の削除
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code/gemm_basic.cpp ファイルの表示

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//Patric Zhao: patric.zhao@gmail.com
#include <chrono>
#include <iostream>
#include <CL/sycl.hpp>
#define random_float() (rand() / double(RAND_MAX))
using namespace std;
using namespace sycl;
// return execution time
double gpu_kernel(float *A, float *B, float *C, int M, int N, int K, int block_size, sycl::queue &q) {
// define the workgroup size and mapping
auto grid_rows = (M + block_size - 1) / block_size * block_size;
auto grid_cols = (N + block_size - 1) / block_size * block_size;
auto local_ndrange = range<2>(block_size, block_size);
auto global_ndrange = range<2>(grid_rows, grid_cols);
double duration = 0.0f;
auto e = q.submit([&](sycl::handler &h) {
h.parallel_for<class k_name_t>(
sycl::nd_range<2>(global_ndrange, local_ndrange), [=](sycl::nd_item<2> index) {
int row = index.get_global_id(0);
int col = index.get_global_id(1);
float sum = 0.0f;
for (int i = 0; i < K; i++) {
sum += A[row * K + i] * B[i * N + col];
}
C[row * N + col] = sum;
});
});
e.wait();
duration += (e.get_profiling_info<info::event_profiling::command_end>() -
e.get_profiling_info<info::event_profiling::command_start>()) /1000.0f/1000.0f;
return(duration);
}
// return execution time
double cpu_kernel(float *cA, float *cB, float *cC, int M, int N, int K) {
double duration = 0.0;
std::chrono::high_resolution_clock::time_point s, e;
// Single Thread Computation in CPU
s = std::chrono::high_resolution_clock::now();
for(int i = 0; i < M; i++) {
for(int j = 0; j < N; j++) {
float sum = 0.0f;
for(int k = 0; k < K; k++) {
sum += cA[i * K + k] * cB[k * N + j];
}
cC[i * N + j] = sum;
}
}
e = std::chrono::high_resolution_clock::now();
duration = std::chrono::duration<float, std::milli>(e - s).count();
return(duration);
}
int verify(float *cpu_res, float *gpu_res, int length){
int err = 0;
for(int i = 0; i < length; i++) {
if( fabs(cpu_res[i] - gpu_res[i]) > 1e-3) {
err++;
printf("\n%lf, %lf", cpu_res[i], gpu_res[i]);
}
}
return(err);
}
int gemm(const int M,
const int N,
const int K,
const int block_size,
const int iterations,
sycl::queue &q) {
cout << "Problem size: c(" << M << "," << N << ") ="
<< " a(" << M << "," << K << ") *"
<< " b(" << K << "," << N << ")\n";
auto A = malloc_shared<float>(M * K, q);
auto B = malloc_shared<float>(K * N, q);
auto C = malloc_shared<float>(M * N, q);
auto C_host = malloc_host<float>(M * N, q);
// init the A/B/C
for(int i=0; i < M * K; i++) {
A[i] = random_float();
}
for(int i=0; i < K * N; i++) {
B[i] = random_float();
}
for(int i=0; i < M * N; i++) {
C[i] = 0.0f;
C_host[i] = 0.0f;
}
double flopsPerMatrixMul
= 2.0 * static_cast<double>(M) * static_cast<double>(N) * static_cast<double>(K);
double duration_gpu = 0.0f;
double duration_cpu = 0.0f;
// GPU compuation and timer
int warmup = 10;
for (int run = 0; run < iterations + warmup; run++) {
float duration = gpu_kernel(A, B, C, M, N, K, block_size, q);
if(run >= warmup) duration_gpu += duration;
}
duration_gpu = duration_gpu / iterations;
// CPU compuation and timer
warmup = 2;
for(int run = 0; run < iterations/2 + warmup; run++) {
float duration = cpu_kernel(A, B, C_host, M, N, K);
if(run >= warmup) duration_cpu += duration;
}
duration_cpu = duration_cpu / iterations/2;
// Compare the resutls of CPU and GPU
int errCode = 0;
errCode = verify(C_host, C, M*N);
if(errCode > 0) printf("\nThere are %d errors\n", errCode);
printf("\nPerformance Flops = %lf, \n"
"GPU Computation Time = %lf (ms); \n"
"CPU Computaiton Time = %lf (ms); \n",
flopsPerMatrixMul, duration_gpu, duration_cpu);
free(A, q);
free(B, q);
free(C, q);
free(C_host, q);
return(errCode);
}
int main() {
auto propList = cl::sycl::property_list {cl::sycl::property::queue::enable_profiling()};
queue my_gpu_queue( cl::sycl::gpu_selector{} , propList);
int errCode = gemm(1024, 1024, 1024, 4, 10, my_gpu_queue);
return(errCode);
}

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