From 23cb35e6c8eae8b59fab161036ae3f417a55c8db Mon Sep 17 00:00:00 2001
From: AlexeyAB <alexeyab84@gmail.com>
Date: Fri, 30 Mar 2018 11:46:51 +0000
Subject: [PATCH] Changed small_object
---
src/gemm.c | 361 ++++++++++++++++++--------------------------------
1 files changed, 132 insertions(+), 229 deletions(-)
diff --git a/src/gemm.c b/src/gemm.c
index 63c2950..c3154ec 100644
--- a/src/gemm.c
+++ b/src/gemm.c
@@ -1,5 +1,66 @@
-#include "mini_blas.h"
+#include "gemm.h"
#include "utils.h"
+#include "cuda.h"
+#include <stdlib.h>
+#include <stdio.h>
+#include <math.h>
+
+void gemm_bin(int M, int N, int K, float ALPHA,
+ char *A, int lda,
+ float *B, int ldb,
+ float *C, int ldc)
+{
+ int i,j,k;
+ for(i = 0; i < M; ++i){
+ for(k = 0; k < K; ++k){
+ char A_PART = A[i*lda+k];
+ if(A_PART){
+ for(j = 0; j < N; ++j){
+ C[i*ldc+j] += B[k*ldb+j];
+ }
+ } else {
+ for(j = 0; j < N; ++j){
+ C[i*ldc+j] -= B[k*ldb+j];
+ }
+ }
+ }
+ }
+}
+
+float *random_matrix(int rows, int cols)
+{
+ int i;
+ float *m = calloc(rows*cols, sizeof(float));
+ for(i = 0; i < rows*cols; ++i){
+ m[i] = (float)rand()/RAND_MAX;
+ }
+ return m;
+}
+
+void time_random_matrix(int TA, int TB, int m, int k, int n)
+{
+ float *a;
+ if(!TA) a = random_matrix(m,k);
+ else a = random_matrix(k,m);
+ int lda = (!TA)?k:m;
+ float *b;
+ if(!TB) b = random_matrix(k,n);
+ else b = random_matrix(n,k);
+ int ldb = (!TB)?n:k;
+
+ float *c = random_matrix(m,n);
+ int i;
+ clock_t start = clock(), end;
+ for(i = 0; i<10; ++i){
+ gemm_cpu(TA,TB,m,n,k,1,a,lda,b,ldb,1,c,n);
+ }
+ end = clock();
+ printf("Matrix Multiplication %dx%d * %dx%d, TA=%d, TB=%d: %lf ms\n",m,k,k,n, TA, TB, (float)(end-start)/CLOCKS_PER_SEC);
+ free(a);
+ free(b);
+ free(c);
+}
+
void gemm(int TA, int TB, int M, int N, int K, float ALPHA,
float *A, int lda,
@@ -90,210 +151,54 @@
C[i*ldc + j] *= BETA;
}
}
- if(!TA && !TB)
- gemm_nn(M, N, K, ALPHA,A,lda, B, ldb,C,ldc);
- else if(TA && !TB)
- gemm_tn(M, N, K, ALPHA,A,lda, B, ldb,C,ldc);
- else if(!TA && TB)
- gemm_nt(M, N, K, ALPHA,A,lda, B, ldb,C,ldc);
- else
- gemm_tt(M, N, K, ALPHA,A,lda, B, ldb,C,ldc);
+
+ int t;
+ #pragma omp parallel for
+ for (t = 0; t < M; ++t) {
+ if (!TA && !TB)
+ gemm_nn(1, N, K, ALPHA, A + t*lda, lda, B, ldb, C + t*ldc, ldc);
+ else if (TA && !TB)
+ gemm_tn(1, N, K, ALPHA, A + t, lda, B, ldb, C + t*ldc, ldc);
+ else if (!TA && TB)
+ gemm_nt(1, N, K, ALPHA, A + t*lda, lda, B, ldb, C + t*ldc, ldc);
+ else
+ gemm_tt(1, N, K, ALPHA, A + t, lda, B, ldb, C + t*ldc, ldc);
+ }
}
#ifdef GPU
-#include "opencl.h"
#include <math.h>
-#include <clBLAS.h>
-
-#define STR_HELPER(x) #x
-#define STR(x) STR_HELPER(x)
-
-#ifdef __APPLE__
-#define BLOCK 1
-#else
-#define BLOCK 16
-#endif
-
-cl_kernel get_gemm_kernel()
-{
- static int init = 0;
- static cl_kernel gemm_kernel;
- if(!init){
- gemm_kernel = get_kernel("src/gemm.cl", "gemm", "-D BLOCK=" STR(BLOCK) );
- init = 1;
- }
- return gemm_kernel;
-}
-
-cl_kernel get_gemm_nt_kernel()
-{
- static int init = 0;
- static cl_kernel gemm_kernel;
- if(!init){
- gemm_kernel = get_kernel("src/gemm_new.cl", "gemm_nt", "-D BLOCK=" STR(BLOCK) );
- init = 1;
- }
- return gemm_kernel;
-}
-
-cl_kernel get_gemm_tn_kernel()
-{
- static int init = 0;
- static cl_kernel gemm_kernel;
- if(!init){
- gemm_kernel = get_kernel("src/gemm_new.cl", "gemm_tn", "-D BLOCK=" STR(BLOCK) );
- init = 1;
- }
- return gemm_kernel;
-}
-
-cl_kernel get_gemm_nn_kernel()
-{
- static int init = 0;
- static cl_kernel gemm_kernel;
- if(!init){
- gemm_kernel = get_kernel("src/gemm_new.cl", "gemm_nn", "-D BLOCK=" STR(BLOCK) );
- init = 1;
- }
- return gemm_kernel;
-}
-
-void gemm_ongpu_new(int TA, int TB, int M, int N, int K, float ALPHA,
- cl_mem A_gpu, int lda,
- cl_mem B_gpu, int ldb,
- float BETA,
- cl_mem C_gpu, int ldc);
-void gemm_ongpu_old(int TA, int TB, int M, int N, int K, float ALPHA,
- cl_mem A_gpu, int lda,
- cl_mem B_gpu, int ldb,
- float BETA,
- cl_mem C_gpu, int ldc);
void gemm_ongpu(int TA, int TB, int M, int N, int K, float ALPHA,
- cl_mem A_gpu, int lda,
- cl_mem B_gpu, int ldb,
+ float *A_gpu, int lda,
+ float *B_gpu, int ldb,
float BETA,
- cl_mem C_gpu, int ldc)
+ float *C_gpu, int ldc)
{
-/*
- cl_setup();
- cl_command_queue queue = cl.queue;
- cl_event event;
- cl.error = clblasSgemm(clblasRowMajor, TA?clblasTrans:clblasNoTrans, TB?clblasTrans:clblasNoTrans,M, N, K,ALPHA, A_gpu, 0, lda,B_gpu, 0, ldb,BETA, C_gpu, 0, ldc,1, &queue, 0, NULL, &event);
-
-*/
- gemm_ongpu_new(TA, TB, M, N, K, ALPHA, A_gpu, lda, B_gpu, ldb, BETA, C_gpu, ldc);
+ cublasHandle_t handle = blas_handle();
+ cudaError_t stream_status = cublasSetStream(handle, get_cuda_stream());
+ cudaError_t status = cublasSgemm(handle, (TB ? CUBLAS_OP_T : CUBLAS_OP_N),
+ (TA ? CUBLAS_OP_T : CUBLAS_OP_N), N, M, K, &ALPHA, B_gpu, ldb, A_gpu, lda, &BETA, C_gpu, ldc);
+ check_error(status);
}
-void gemm_ongpu_new(int TA, int TB, int M, int N, int K, float ALPHA,
- cl_mem A_gpu, int lda,
- cl_mem B_gpu, int ldb,
- float BETA,
- cl_mem C_gpu, int ldc)
-{
- //printf("gpu: %d %d %d %d %d\n",TA, TB, M, N, K);
- cl_setup();
- cl_kernel gemm_kernel = get_gemm_kernel();
- if(!TA && !TB) gemm_kernel = get_gemm_nn_kernel();
- if(!TA && TB) gemm_kernel = get_gemm_nt_kernel();
- if(TA && !TB) gemm_kernel = get_gemm_tn_kernel();
- cl_command_queue queue = cl.queue;
-
- cl_uint i = 0;
- cl.error = clSetKernelArg(gemm_kernel, i++, sizeof(TA), (void*) &TA);
- cl.error = clSetKernelArg(gemm_kernel, i++, sizeof(TB), (void*) &TB);
- cl.error = clSetKernelArg(gemm_kernel, i++, sizeof(M), (void*) &M);
- cl.error = clSetKernelArg(gemm_kernel, i++, sizeof(N), (void*) &N);
- cl.error = clSetKernelArg(gemm_kernel, i++, sizeof(K), (void*) &K);
- cl.error = clSetKernelArg(gemm_kernel, i++, sizeof(ALPHA), (void*) &ALPHA);
- cl.error = clSetKernelArg(gemm_kernel, i++, sizeof(A_gpu), (void*) &A_gpu);
- cl.error = clSetKernelArg(gemm_kernel, i++, sizeof(lda), (void*) &lda);
- cl.error = clSetKernelArg(gemm_kernel, i++, sizeof(B_gpu), (void*) &B_gpu);
- cl.error = clSetKernelArg(gemm_kernel, i++, sizeof(ldb), (void*) &ldb);
- cl.error = clSetKernelArg(gemm_kernel, i++, sizeof(BETA), (void*) &BETA);
- cl.error = clSetKernelArg(gemm_kernel, i++, sizeof(C_gpu), (void*) &C_gpu);
- cl.error = clSetKernelArg(gemm_kernel, i++, sizeof(ldc), (void*) &ldc);
- check_error(cl);
-
- const size_t global_size[] = {ceil((float)N/BLOCK)*BLOCK, ceil((float)M/BLOCK)*BLOCK};
- const size_t local_size[] = {BLOCK, BLOCK};
-
- clEnqueueNDRangeKernel(queue, gemm_kernel, 2, 0, global_size, local_size, 0, 0, 0);
- check_error(cl);
-}
-
-void gemm_ongpu_old(int TA, int TB, int M, int N, int K, float ALPHA,
- cl_mem A_gpu, int lda,
- cl_mem B_gpu, int ldb,
- float BETA,
- cl_mem C_gpu, int ldc)
-{
- //printf("gpu: %d %d %d %d %d\n",TA, TB, M, N, K);
- cl_setup();
- cl_kernel gemm_kernel = get_gemm_kernel();
- cl_command_queue queue = cl.queue;
-
- cl_uint i = 0;
- cl.error = clSetKernelArg(gemm_kernel, i++, sizeof(TA), (void*) &TA);
- cl.error = clSetKernelArg(gemm_kernel, i++, sizeof(TB), (void*) &TB);
- cl.error = clSetKernelArg(gemm_kernel, i++, sizeof(M), (void*) &M);
- cl.error = clSetKernelArg(gemm_kernel, i++, sizeof(N), (void*) &N);
- cl.error = clSetKernelArg(gemm_kernel, i++, sizeof(K), (void*) &K);
- cl.error = clSetKernelArg(gemm_kernel, i++, sizeof(ALPHA), (void*) &ALPHA);
- cl.error = clSetKernelArg(gemm_kernel, i++, sizeof(A_gpu), (void*) &A_gpu);
- cl.error = clSetKernelArg(gemm_kernel, i++, sizeof(lda), (void*) &lda);
- cl.error = clSetKernelArg(gemm_kernel, i++, sizeof(B_gpu), (void*) &B_gpu);
- cl.error = clSetKernelArg(gemm_kernel, i++, sizeof(ldb), (void*) &ldb);
- cl.error = clSetKernelArg(gemm_kernel, i++, sizeof(BETA), (void*) &BETA);
- cl.error = clSetKernelArg(gemm_kernel, i++, sizeof(C_gpu), (void*) &C_gpu);
- cl.error = clSetKernelArg(gemm_kernel, i++, sizeof(ldc), (void*) &ldc);
- check_error(cl);
-
- const size_t global_size[] = {ceil((float)N/BLOCK)*BLOCK, ceil((float)M/BLOCK)*BLOCK};
- const size_t local_size[] = {BLOCK, BLOCK};
-
- clEnqueueNDRangeKernel(queue, gemm_kernel, 2, 0, global_size, local_size, 0, 0, 0);
- check_error(cl);
-}
-
-
void gemm_gpu(int TA, int TB, int M, int N, int K, float ALPHA,
float *A, int lda,
float *B, int ldb,
float BETA,
float *C, int ldc)
{
- cl_setup();
- cl_context context = cl.context;
- cl_command_queue queue = cl.queue;
-
- size_t size = sizeof(float)*(TA ? lda*K:lda*M);
- cl_mem A_gpu = clCreateBuffer(context,
- CL_MEM_READ_ONLY|CL_MEM_COPY_HOST_PTR,
- size, A, &cl.error);
- check_error(cl);
-
- size = sizeof(float)*(TB ? ldb*N:ldb*K);
- cl_mem B_gpu = clCreateBuffer(context,
- CL_MEM_READ_ONLY|CL_MEM_COPY_HOST_PTR,
- size, B, &cl.error);
- check_error(cl);
-
- size = sizeof(float)*(ldc*M);
- cl_mem C_gpu = clCreateBuffer(context,
- CL_MEM_READ_WRITE|CL_MEM_COPY_HOST_PTR,
- size, C, &cl.error);
- check_error(cl);
+ float *A_gpu = cuda_make_array(A, (TA ? lda*K:lda*M));
+ float *B_gpu = cuda_make_array(B, (TB ? ldb*N : ldb*K));
+ float *C_gpu = cuda_make_array(C, ldc*M);
gemm_ongpu(TA, TB, M, N, K, ALPHA, A_gpu, lda, B_gpu, ldb, BETA, C_gpu, ldc);
- clEnqueueReadBuffer(queue, C_gpu, CL_TRUE, 0, size, C, 0, 0, 0);
- check_error(cl);
-
- clReleaseMemObject(A_gpu);
- clReleaseMemObject(B_gpu);
- clReleaseMemObject(C_gpu);
+ cuda_pull_array(C_gpu, C, ldc*M);
+ cuda_free(A_gpu);
+ cuda_free(B_gpu);
+ cuda_free(C_gpu);
}
#include <stdio.h>
@@ -327,7 +232,7 @@
void time_ongpu(int TA, int TB, int m, int k, int n)
{
- int iter = 128;
+ int iter = 10;
float *a = random_matrix(m,k);
float *b = random_matrix(k,n);
@@ -336,28 +241,30 @@
float *c = random_matrix(m,n);
- cl_mem a_cl = cl_make_array(a, m*k);
- cl_mem b_cl = cl_make_array(b, k*n);
- cl_mem c_cl = cl_make_array(c, m*n);
+ float *a_cl = cuda_make_array(a, m*k);
+ float *b_cl = cuda_make_array(b, k*n);
+ float *c_cl = cuda_make_array(c, m*n);
int i;
clock_t start = clock(), end;
for(i = 0; i<iter; ++i){
gemm_ongpu(TA,TB,m,n,k,1,a_cl,lda,b_cl,ldb,1,c_cl,n);
+ cudaThreadSynchronize();
}
- double flop = m*n*(2.*k+3.)*iter;
+ double flop = ((double)m)*n*(2.*k + 2.)*iter;
double gflop = flop/pow(10., 9);
end = clock();
double seconds = sec(end-start);
printf("Matrix Multiplication %dx%d * %dx%d, TA=%d, TB=%d: %lf s, %lf GFLOPS\n",m,k,k,n, TA, TB, seconds, gflop/seconds);
- clReleaseMemObject(a_cl);
- clReleaseMemObject(b_cl);
- clReleaseMemObject(c_cl);
+ cuda_free(a_cl);
+ cuda_free(b_cl);
+ cuda_free(c_cl);
free(a);
free(b);
free(c);
}
+
void test_gpu_accuracy(int TA, int TB, int m, int k, int n)
{
srand(0);
@@ -377,8 +284,11 @@
int i;
//pm(m,k,b);
gemm_gpu(TA,TB,m,n,k,1,a,lda,b,ldb,1,c_gpu,n);
+ //printf("GPU\n");
//pm(m, n, c_gpu);
+
gemm_cpu(TA,TB,m,n,k,1,a,lda,b,ldb,1,c,n);
+ //printf("\n\nCPU\n");
//pm(m, n, c);
double sse = 0;
for(i = 0; i < m*n; ++i) {
@@ -392,50 +302,43 @@
free(c_gpu);
}
-void test_gpu_blas()
+int test_gpu_blas()
{
/*
- test_gpu_accuracy(0,0,10,576,75);
+ test_gpu_accuracy(0,0,10,576,75);
- test_gpu_accuracy(0,0,17,10,10);
- test_gpu_accuracy(1,0,17,10,10);
- test_gpu_accuracy(0,1,17,10,10);
- test_gpu_accuracy(1,1,17,10,10);
+ test_gpu_accuracy(0,0,17,10,10);
+ test_gpu_accuracy(1,0,17,10,10);
+ test_gpu_accuracy(0,1,17,10,10);
+ test_gpu_accuracy(1,1,17,10,10);
- test_gpu_accuracy(0,0,1000,10,100);
- test_gpu_accuracy(1,0,1000,10,100);
- test_gpu_accuracy(0,1,1000,10,100);
- test_gpu_accuracy(1,1,1000,10,100);
- */
- test_gpu_accuracy(0,0,131,4093,1199);
- test_gpu_accuracy(0,1,131,4093,1199);
- test_gpu_accuracy(1,0,131,4093,1199);
- test_gpu_accuracy(1,1,131,4093,1199);
+ test_gpu_accuracy(0,0,1000,10,100);
+ test_gpu_accuracy(1,0,1000,10,100);
+ test_gpu_accuracy(0,1,1000,10,100);
+ test_gpu_accuracy(1,1,1000,10,100);
- time_ongpu(0,0,1024,1024,1024);
- time_ongpu(0,1,1024,1024,1024);
- time_ongpu(1,0,1024,1024,1024);
- time_ongpu(1,1,1024,1024,1024);
+ test_gpu_accuracy(0,0,10,10,10);
- time_ongpu(0,0,128,4096,1200);
- time_ongpu(0,1,128,4096,1200);
- time_ongpu(1,0,128,4096,1200);
- time_ongpu(1,1,128,4096,1200);
-
- /*
- time_gpu_random_matrix(0,0,1000,1000,100);
- time_random_matrix(0,0,1000,1000,100);
-
- time_gpu_random_matrix(0,1,1000,1000,100);
- time_random_matrix(0,1,1000,1000,100);
-
- time_gpu_random_matrix(1,0,1000,1000,100);
- time_random_matrix(1,0,1000,1000,100);
-
- time_gpu_random_matrix(1,1,1000,1000,100);
- time_random_matrix(1,1,1000,1000,100);
+ time_ongpu(0,0,64,2916,363);
+ time_ongpu(0,0,64,2916,363);
+ time_ongpu(0,0,64,2916,363);
+ time_ongpu(0,0,192,729,1600);
+ time_ongpu(0,0,384,196,1728);
+ time_ongpu(0,0,256,196,3456);
+ time_ongpu(0,0,256,196,2304);
+ time_ongpu(0,0,128,4096,12544);
+ time_ongpu(0,0,128,4096,4096);
*/
+ time_ongpu(0,0,64,75,12544);
+ time_ongpu(0,0,64,75,12544);
+ time_ongpu(0,0,64,75,12544);
+ time_ongpu(0,0,64,576,12544);
+ time_ongpu(0,0,256,2304,784);
+ time_ongpu(1,1,2304,256,784);
+ time_ongpu(0,0,512,4608,196);
+ time_ongpu(1,1,4608,512,196);
+ return 0;
}
#endif
--
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