| | |
| | | |
| | | #include <stdlib.h> |
| | | #include <stdio.h> |
| | | #include <math.h> |
| | |
| | | printf("\n"); |
| | | } |
| | | |
| | | void gemm(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) |
| | | { |
| | | gpu_gemm( TA, TB, M, N, K, ALPHA,A,lda, B, ldb,BETA,C,ldc); |
| | | } |
| | | |
| | | void im2row(float *image, int h, int w, int c, int size, int stride, float *matrix) |
| | | { |
| | | int i; |
| | | int mc = c; |
| | | int mw = (size*size); |
| | | int mh = ((h-size)/stride+1)*((w-size)/stride+1); |
| | | int msize = mc*mw*mh; |
| | | for(i = 0; i < msize; ++i){ |
| | | int channel = i/(mh*mw); |
| | | int block = (i%(mh*mw))/mw; |
| | | int position = i%mw; |
| | | int block_h = block/((w-size)/stride+1); |
| | | int block_w = block%((w-size)/stride+1); |
| | | int ph, pw, pc; |
| | | ph = position/size+block_h; |
| | | pw = position%size+block_w; |
| | | pc = channel; |
| | | matrix[i] = image[pc*h*w+ph*w+pw]; |
| | | } |
| | | } |
| | | void im2col(float *image, int h, int w, int c, int size, int stride, float *matrix) |
| | | { |
| | | int b,p; |
| | | int blocks = ((h-size)/stride+1)*((w-size)/stride+1); |
| | | int pixels = (size*size*c); |
| | | for(b = 0; b < blocks; ++b){ |
| | | int block_h = b/((w-size)/stride+1); |
| | | int block_w = b%((w-size)/stride+1); |
| | | for(p = 0; p < pixels; ++p){ |
| | | int ph, pw, pc; |
| | | int position = p%(size*size); |
| | | pc = p/(size*size); |
| | | ph = position/size+block_h; |
| | | pw = position%size+block_w; |
| | | matrix[b+p*blocks] = image[pc*h*w+ph*w+pw]; |
| | | } |
| | | } |
| | | } |
| | | |
| | | //From Berkeley Vision's Caffe! |
| | | void im2col_cpu(float* data_im, const int channels, |
| | | const int height, const int width, const int ksize, const int stride, |
| | | float* data_col) |
| | | { |
| | | int c,h,w; |
| | | int height_col = (height - ksize) / stride + 1; |
| | | int width_col = (width - ksize) / stride + 1; |
| | | int channels_col = channels * ksize * ksize; |
| | | for ( c = 0; c < channels_col; ++c) { |
| | | int w_offset = c % ksize; |
| | | int h_offset = (c / ksize) % ksize; |
| | | int c_im = c / ksize / ksize; |
| | | for ( h = 0; h < height_col; ++h) { |
| | | for ( w = 0; w < width_col; ++w) { |
| | | data_col[(c * height_col + h) * width_col + w] = |
| | | data_im[(c_im * height + h * stride + h_offset) * width |
| | | + w * stride + w_offset]; |
| | | } |
| | | } |
| | | } |
| | | } |
| | | |
| | | void col2im_cpu(float* data_col, const int channels, |
| | | const int height, const int width, const int ksize, const int stride, |
| | | float* data_im) |
| | | { |
| | | int c,h,w; |
| | | int height_col = (height - ksize) / stride + 1; |
| | | int width_col = (width - ksize) / stride + 1; |
| | | int channels_col = channels * ksize * ksize; |
| | | for ( c = 0; c < channels_col; ++c) { |
| | | int w_offset = c % ksize; |
| | | int h_offset = (c / ksize) % ksize; |
| | | int c_im = c / ksize / ksize; |
| | | for ( h = 0; h < height_col; ++h) { |
| | | for ( w = 0; w < width_col; ++w) { |
| | | data_im[(c_im * height + h * stride + h_offset) * width |
| | | + w * stride + w_offset]+= data_col[(c * height_col + h) * width_col + w]; |
| | | } |
| | | } |
| | | } |
| | | } |
| | | |
| | | float *random_matrix(int rows, int cols) |
| | | { |
| | | int i; |
| | |
| | | float *c = random_matrix(m,n); |
| | | int i; |
| | | clock_t start = clock(), end; |
| | | for(i = 0; i<1000; ++i){ |
| | | cpu_gemm(TA,TB,m,n,k,1,a,lda,b,ldb,1,c,n); |
| | | 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); |
| | |
| | | |
| | | void test_blas() |
| | | { |
| | | |
| | | time_random_matrix(0,0,100,100,100); |
| | | time_random_matrix(1,0,100,100,100); |
| | | time_random_matrix(0,1,100,100,100); |