chundoong-lab-ta/APWS23/matmul-skeleton/matmul_cublas.cpp

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#include <cublas_v2.h>
#include <cuda_runtime_api.h>
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#include <cstdio>
#include <cstdlib>
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#include "matmul.h"
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#define CHECK_CUDA(call) \
do { \
cudaError_t status_ = call; \
if (status_ != cudaSuccess) { \
fprintf(stderr, "CUDA error (%s:%d): %s\n", __FILE__, __LINE__, \
cudaGetErrorString(status_)); \
exit(EXIT_FAILURE); \
} \
} while (0)
#define CHECK_CUBLAS(call) \
do { \
cublasStatus_t status_ = call; \
if (status_ != CUBLAS_STATUS_SUCCESS) { \
fprintf(stderr, "CUBLAS error (%s:%d): %s, %s\n", __FILE__, __LINE__, \
cublasGetStatusName(status_), cublasGetStatusString(status_)); \
exit(EXIT_FAILURE); \
} \
} while (0)
static float *A_gpu, *B_gpu, *C_gpu;
static cublasHandle_t handle;
void matmul_cublas_initialize(size_t M, size_t N, size_t K) {
// TODO: Implement here
// 1. Create cublas handle
CHECK_CUBLAS(cublasCreate(&handle));
// 2. Allocate GPU memory for A, B, C
// cudaMalloc(&A_gpu, ...);
// cudaMalloc(&B_gpu, ...);
// cudaMalloc(&C_gpu, ...);
}
void matmul_cublas(float *A, float *B, float *C, size_t M, size_t N, size_t K) {
// TODO: Implement here
// 1. Send A from CPU to GPU
// cublasSetMatrix(...);
// 2. Send B from CPU to GPU
// cublasSetMatrix(...);
// 3. Run SGEMM
const float one = 1, zero = 0;
// cublasSgemm(handle, ...);
// 4. Send C from GPU to CPU
// cublasGetMatrix(...);
}
void matmul_cublas_finalize(size_t M, size_t N, size_t K) {
// TODO: Implement here
// 1. Free GPU memory for A, B, C
// cudaFree(...);
// cudaFree(...);
// cudaFree(...);
// 2. Destroy cublas handle
// cublasDestroy(...);
}