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https://github.com/pjreddie/darknet.git
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GPU flag in Makefile
This commit is contained in:
parent
324e0a33dd
commit
354b0cbdcb
10
Makefile
10
Makefile
@ -1,21 +1,29 @@
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CC=gcc
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CC=gcc
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GPU=0
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COMMON=-Wall `pkg-config --cflags opencv` -I/usr/local/cuda/include/
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COMMON=-Wall `pkg-config --cflags opencv` -I/usr/local/cuda/include/
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UNAME = $(shell uname)
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UNAME = $(shell uname)
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OPTS=-O3
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OPTS=-O3
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ifeq ($(UNAME), Darwin)
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ifeq ($(UNAME), Darwin)
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COMMON+= -isystem /usr/local/Cellar/opencv/2.4.6.1/include/opencv -isystem /usr/local/Cellar/opencv/2.4.6.1/include
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COMMON+= -isystem /usr/local/Cellar/opencv/2.4.6.1/include/opencv -isystem /usr/local/Cellar/opencv/2.4.6.1/include
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ifeq ($(GPU), 1)
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LDFLAGS= -framework OpenCL
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LDFLAGS= -framework OpenCL
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endif
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else
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else
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OPTS+= -march=native
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OPTS+= -march=native
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ifeq ($(GPU), 1)
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LDFLAGS= -lOpenCL
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LDFLAGS= -lOpenCL
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endif
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endif
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endif
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CFLAGS= $(COMMON) $(OPTS)
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CFLAGS= $(COMMON) $(OPTS)
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#CFLAGS= $(COMMON) -O0 -g
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#CFLAGS= $(COMMON) -O0 -g
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LDFLAGS+=`pkg-config --libs opencv` -lm
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LDFLAGS+=`pkg-config --libs opencv` -lm
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VPATH=./src/
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VPATH=./src/
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EXEC=cnn
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EXEC=cnn
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OBJ=network.o image.o tests.o connected_layer.o maxpool_layer.o activations.o list.o option_list.o parser.o utils.o data.o matrix.o softmax_layer.o mini_blas.o convolutional_layer.o opencl.o gpu_gemm.o cpu_gemm.o normalization_layer.o
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OBJ=network.o image.o tests.o connected_layer.o maxpool_layer.o activations.o list.o option_list.o parser.o utils.o data.o matrix.o softmax_layer.o mini_blas.o convolutional_layer.o cpu_gemm.o normalization_layer.o
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ifeq ($(GPU), 1)
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OBJ+=gpu_gemm.o opencl.o
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endif
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all: $(EXEC)
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all: $(EXEC)
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@ -83,6 +83,89 @@ void gpu_gemm(int TA, int TB, int M, int N, int K, float ALPHA,
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}
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}
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void time_gpu_random_matrix(int TA, int TB, int m, int k, int n)
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{
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float *a;
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if(!TA) a = random_matrix(m,k);
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else a = random_matrix(k,m);
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int lda = (!TA)?k:m;
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float *b;
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if(!TB) b = random_matrix(k,n);
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else b = random_matrix(n,k);
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int ldb = (!TB)?n:k;
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float *c = random_matrix(m,n);
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int i;
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clock_t start = clock(), end;
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for(i = 0; i<1000; ++i){
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gpu_gemm(TA,TB,m,n,k,1,a,lda,b,ldb,1,c,n);
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}
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end = clock();
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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);
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free(a);
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free(b);
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free(c);
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}
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void test_gpu_accuracy(int TA, int TB, int m, int k, int n)
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{
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srand(0);
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float *a;
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if(!TA) a = random_matrix(m,k);
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else a = random_matrix(k,m);
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int lda = (!TA)?k:m;
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float *b;
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if(!TB) b = random_matrix(k,n);
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else b = random_matrix(n,k);
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int ldb = (!TB)?n:k;
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float *c = random_matrix(m,n);
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float *c_gpu = random_matrix(m,n);
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memset(c, 0, m*n*sizeof(float));
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memset(c_gpu, 0, m*n*sizeof(float));
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int i;
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//pm(m,k,b);
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gpu_gemm(TA,TB,m,n,k,1,a,lda,b,ldb,1,c_gpu,n);
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//pm(m, n, c_gpu);
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cpu_gemm(TA,TB,m,n,k,1,a,lda,b,ldb,1,c,n);
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//pm(m, n, c);
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double sse = 0;
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for(i = 0; i < m*n; ++i) {
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//printf("%f %f\n", c[i], c_gpu[i]);
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sse += pow(c[i]-c_gpu[i], 2);
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}
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printf("Matrix Multiplication %dx%d * %dx%d, TA=%d, TB=%d: %g MSE\n",m,k,k,n, TA, TB, sse/(m*n));
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free(a);
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free(b);
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free(c);
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}
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void test_gpu_blas()
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{
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test_gpu_accuracy(0,0,17,10,10);
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test_gpu_accuracy(1,0,17,10,10);
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test_gpu_accuracy(0,1,17,10,10);
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test_gpu_accuracy(1,1,17,10,10);
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test_gpu_accuracy(0,0,1000,10,100);
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test_gpu_accuracy(1,0,1000,10,100);
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test_gpu_accuracy(0,1,1000,10,100);
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test_gpu_accuracy(1,1,1000,10,100);
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time_gpu_random_matrix(0,0,1000,1000,100);
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time_random_matrix(0,0,1000,1000,100);
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time_gpu_random_matrix(0,1,1000,1000,100);
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time_random_matrix(0,1,1000,1000,100);
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time_gpu_random_matrix(1,0,1000,1000,100);
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time_random_matrix(1,0,1000,1000,100);
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time_gpu_random_matrix(1,1,1000,1000,100);
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time_random_matrix(1,1,1000,1000,100);
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}
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/*
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/*
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cl_kernel get_gemm_kernel_slow()
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cl_kernel get_gemm_kernel_slow()
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{
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{
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@ -24,7 +24,7 @@ void gemm(int TA, int TB, int M, int N, int K, float ALPHA,
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float BETA,
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float BETA,
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float *C, int ldc)
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float *C, int ldc)
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{
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{
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gpu_gemm( TA, TB, M, N, K, ALPHA,A,lda, B, ldb,BETA,C,ldc);
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cpu_gemm( TA, TB, M, N, K, ALPHA,A,lda, B, ldb,BETA,C,ldc);
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}
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}
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void im2row(float *image, int h, int w, int c, int size, int stride, float *matrix)
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void im2row(float *image, int h, int w, int c, int size, int stride, float *matrix)
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@ -155,91 +155,5 @@ void test_blas()
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time_random_matrix(1,0,1000,100,100);
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time_random_matrix(1,0,1000,100,100);
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time_random_matrix(0,1,1000,100,100);
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time_random_matrix(0,1,1000,100,100);
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time_random_matrix(1,1,1000,100,100);
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time_random_matrix(1,1,1000,100,100);
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}
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}
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void time_gpu_random_matrix(int TA, int TB, int m, int k, int n)
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{
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float *a;
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if(!TA) a = random_matrix(m,k);
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else a = random_matrix(k,m);
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int lda = (!TA)?k:m;
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float *b;
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if(!TB) b = random_matrix(k,n);
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else b = random_matrix(n,k);
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int ldb = (!TB)?n:k;
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float *c = random_matrix(m,n);
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int i;
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clock_t start = clock(), end;
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for(i = 0; i<1000; ++i){
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gpu_gemm(TA,TB,m,n,k,1,a,lda,b,ldb,1,c,n);
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}
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end = clock();
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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);
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free(a);
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free(b);
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free(c);
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}
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void test_gpu_accuracy(int TA, int TB, int m, int k, int n)
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{
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srand(0);
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float *a;
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if(!TA) a = random_matrix(m,k);
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else a = random_matrix(k,m);
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int lda = (!TA)?k:m;
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float *b;
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if(!TB) b = random_matrix(k,n);
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else b = random_matrix(n,k);
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int ldb = (!TB)?n:k;
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float *c = random_matrix(m,n);
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float *c_gpu = random_matrix(m,n);
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memset(c, 0, m*n*sizeof(float));
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memset(c_gpu, 0, m*n*sizeof(float));
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int i;
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//pm(m,k,b);
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gpu_gemm(TA,TB,m,n,k,1,a,lda,b,ldb,1,c_gpu,n);
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//pm(m, n, c_gpu);
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cpu_gemm(TA,TB,m,n,k,1,a,lda,b,ldb,1,c,n);
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//pm(m, n, c);
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double sse = 0;
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for(i = 0; i < m*n; ++i) {
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//printf("%f %f\n", c[i], c_gpu[i]);
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sse += pow(c[i]-c_gpu[i], 2);
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}
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printf("Matrix Multiplication %dx%d * %dx%d, TA=%d, TB=%d: %g MSE\n",m,k,k,n, TA, TB, sse/(m*n));
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free(a);
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free(b);
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free(c);
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}
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void test_gpu_blas()
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{
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test_gpu_accuracy(0,0,17,10,10);
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test_gpu_accuracy(1,0,17,10,10);
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test_gpu_accuracy(0,1,17,10,10);
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test_gpu_accuracy(1,1,17,10,10);
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test_gpu_accuracy(0,0,1000,10,100);
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test_gpu_accuracy(1,0,1000,10,100);
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test_gpu_accuracy(0,1,1000,10,100);
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test_gpu_accuracy(1,1,1000,10,100);
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time_gpu_random_matrix(0,0,1000,1000,100);
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time_random_matrix(0,0,1000,1000,100);
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time_gpu_random_matrix(0,1,1000,1000,100);
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time_random_matrix(0,1,1000,1000,100);
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time_gpu_random_matrix(1,0,1000,1000,100);
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time_random_matrix(1,0,1000,1000,100);
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time_gpu_random_matrix(1,1,1000,1000,100);
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time_random_matrix(1,1,1000,1000,100);
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}
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@ -789,9 +789,9 @@ int main(int argc, char *argv[])
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//test_vince();
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//test_vince();
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//test_full();
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//test_full();
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//train_VOC();
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//train_VOC();
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features_VOC_image(argv[1], argv[2], argv[3], 0);
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//features_VOC_image(argv[1], argv[2], argv[3], 0);
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features_VOC_image(argv[1], argv[2], argv[3], 1);
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//features_VOC_image(argv[1], argv[2], argv[3], 1);
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//features_VOC_image_size(argv[1], atoi(argv[2]), atoi(argv[3]));
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features_VOC_image_size(argv[1], atoi(argv[2]), atoi(argv[3]));
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//visualize_imagenet_features("data/assira/train.list");
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//visualize_imagenet_features("data/assira/train.list");
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//visualize_imagenet_topk("data/VOC2012.list");
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//visualize_imagenet_topk("data/VOC2012.list");
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//visualize_cat();
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//visualize_cat();
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