36676f2d1b
SGEMM repos (upstream_ref/sgemm_cuda/, 41 files): siboehm/SGEMM_CUDA: kernel 1-12, runner, CMake, cuBLAS benchmark wangzyon/NVIDIA_SGEMM_PRACTICE: kernel 1-7 (Chinese comments), utils edtallison/sgemm-cuda: kernel 01-09 (learning notes), Makefile xllm kernels (ex_engine/xllm_kernels/cuda/): fused_qknorm_rope.cu + bind — saves 128 kernel launches/fwd xattention/ — 6 files from upstream xllm headers: corex_compat_utils.h, topk_last_dim.cuh ilu/CMakeLists.txt SO_BUILD_MANIFEST.md — complete .so inventory and call chain analysis
108 lines
2.5 KiB
Plaintext
108 lines
2.5 KiB
Plaintext
#include <cstdio>
|
|
#include <cublas_v2.h>
|
|
#include <cuda_runtime.h>
|
|
|
|
/*
|
|
* A stand-alone script to invoke & benchmark standard cuBLAS SGEMM performance
|
|
*/
|
|
|
|
int main(int argc, char *argv[]) {
|
|
int m = 2;
|
|
int k = 3;
|
|
int n = 4;
|
|
int print = 1;
|
|
cudaError_t cudaStat; // cudaMalloc status
|
|
cublasStatus_t stat; // cuBLAS functions status
|
|
cublasHandle_t handle; // cuBLAS context
|
|
|
|
int i, j;
|
|
|
|
float *a, *b, *c;
|
|
|
|
// malloc for a,b,c...
|
|
a = (float *)malloc(m * k * sizeof(float));
|
|
b = (float *)malloc(k * n * sizeof(float));
|
|
c = (float *)malloc(m * n * sizeof(float));
|
|
|
|
int ind = 11;
|
|
for (j = 0; j < m * k; j++) {
|
|
a[j] = (float)ind++;
|
|
}
|
|
|
|
ind = 11;
|
|
for (j = 0; j < k * n; j++) {
|
|
b[j] = (float)ind++;
|
|
}
|
|
|
|
ind = 11;
|
|
for (j = 0; j < m * n; j++) {
|
|
c[j] = (float)ind++;
|
|
}
|
|
|
|
// DEVICE
|
|
float *d_a, *d_b, *d_c;
|
|
|
|
// cudaMalloc for d_a, d_b, d_c...
|
|
cudaMalloc((void **)&d_a, m * k * sizeof(float));
|
|
cudaMalloc((void **)&d_b, k * n * sizeof(float));
|
|
cudaMalloc((void **)&d_c, m * n * sizeof(float));
|
|
|
|
stat = cublasCreate(&handle); // initialize CUBLAS context
|
|
|
|
cudaMemcpy(d_a, a, m * k * sizeof(float), cudaMemcpyHostToDevice);
|
|
cudaMemcpy(d_b, b, k * n * sizeof(float), cudaMemcpyHostToDevice);
|
|
cudaMemcpy(d_c, c, m * n * sizeof(float), cudaMemcpyHostToDevice);
|
|
|
|
float alpha = 1.0f;
|
|
float beta = 0.5f;
|
|
|
|
if (print == 1) {
|
|
printf("alpha = %4.0f, beta = %4.0f\n", alpha, beta);
|
|
printf("A = (mxk: %d x %d)\n", m, k);
|
|
for (i = 0; i < m; i++) {
|
|
for (j = 0; j < k; j++) {
|
|
printf("%4.1f ", a[i * m + j]);
|
|
}
|
|
printf("\n");
|
|
}
|
|
printf("B = (kxn: %d x %d)\n", k, n);
|
|
for (i = 0; i < k; i++) {
|
|
for (j = 0; j < n; j++) {
|
|
printf("%4.1f ", b[i * n + j]);
|
|
}
|
|
printf("\n");
|
|
}
|
|
printf("C = (mxn: %d x %d)\n", m, n);
|
|
for (i = 0; i < m; i++) {
|
|
for (j = 0; j < n; j++) {
|
|
printf("%4.1f ", c[i * n + j]);
|
|
}
|
|
printf("\n");
|
|
}
|
|
}
|
|
|
|
stat = cublasSgemm(handle, CUBLAS_OP_N, CUBLAS_OP_N, n, m, k, &alpha, d_b, n,
|
|
d_a, k, &beta, d_c, n);
|
|
|
|
cudaMemcpy(c, d_c, m * n * sizeof(float), cudaMemcpyDeviceToHost);
|
|
|
|
if (print == 1) {
|
|
printf("\nC after SGEMM = \n");
|
|
for (i = 0; i < m; i++) {
|
|
for (j = 0; j < n; j++) {
|
|
printf("%4.1f ", c[i * n + j]);
|
|
}
|
|
printf("\n");
|
|
}
|
|
}
|
|
|
|
cudaFree(d_a);
|
|
cudaFree(d_b);
|
|
cudaFree(d_c);
|
|
cublasDestroy(handle); // destroy CUBLAS context
|
|
free(a);
|
|
free(b);
|
|
free(c);
|
|
|
|
return EXIT_SUCCESS;
|
|
} |