284804ac53
Sources: siboehm/SGEMM_CUDA → upstream_ref/sgemm_siboehm/ (25 files) wangzyon/NVIDIA_SGEMM_PRACTICE → upstream_ref/nvidia_sgemm_practice/ (23 files, filled gaps) edtallison/sgemm-cuda → upstream_ref/sgemm_edtallison/ (41 files) All files cat'd one by one from git clone (no --depth). These are the 3 public SGEMM repos that can compile on CUDA 10.2 + CoreX ivcore10. Key files for BI-V100 porting: kernel 10 (warp tiling) — already proven on device with WARPSIZE=64 kernel 11/12 (double buffering) — next optimization target sgemm.cu + runner.cu — complete build+benchmark harness CMakeLists.txt — build system reference
42 lines
1.3 KiB
Plaintext
42 lines
1.3 KiB
Plaintext
#pragma once
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#include <stdio.h>
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#include <stdlib.h>
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#include <time.h>
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#include <unistd.h>
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#include <sys/time.h>
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#include <cuda_runtime.h>
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#include <cublas_v2.h>
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/*
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=====================================
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CUDA操作
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=====================================
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*/
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void cudaCheck(cudaError_t error, const char *file, int line); //CUDA错误检查
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void CudaDeviceInfo(); // 打印CUDA信息
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/*
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=====================================
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矩阵操作
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=====================================
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*/
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void randomize_matrix(float *mat, int N); // 随机初始化矩阵
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void copy_matrix(float *src, float *dest, int N); // 复制矩阵
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void print_matrix(const float *A, int M, int N); // 打印矩阵
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bool verify_matrix(float *mat1, float *mat2, int N); // 验证矩阵
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/*
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=====================================
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计时操作
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=====================================
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*/
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float get_current_sec(); // 获取当前时刻
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float cpu_elapsed_time(float &beg, float &end); // 计算时间差
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/*
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=====================================
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kernel操作
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=====================================
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*/
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//调用指定核函数计算矩阵乘法
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void test_kernel(int kernel_num, int m, int n, int k, float alpha, float *A, float *B, float beta, float *C, cublasHandle_t handle); |