diff --git a/src/gemm.c b/src/gemm.c index 478e9663..ff5edfa9 100644 --- a/src/gemm.c +++ b/src/gemm.c @@ -1,1210 +1,1217 @@ -#include "gemm.h" -#include "utils.h" -#include "im2col.h" -#include "cuda.h" -#include -#include -#include - -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, - float *B, int ldb, - float BETA, - float *C, int ldc) -{ - gemm_cpu( TA, TB, M, N, K, ALPHA,A,lda, B, ldb,BETA,C,ldc); -} - - -//-------------------------------------------- -// XNOR bitwise GEMM for binary neural network -//-------------------------------------------- - -#include - -static inline unsigned char xnor(unsigned char a, unsigned char b) { - //return a == b; - return !(a^b); -} - -// INT-32 -static inline uint32_t get_bit_int32(uint32_t const*const src, size_t index) { - size_t src_i = index / 32; - int src_shift = index % 32; - unsigned char val = (src[src_i] & (1 << src_shift)) > 0; - return val; -} - -static inline uint32_t xnor_int32(uint32_t a, uint32_t b) { - return ~(a^b); -} - -static inline uint64_t xnor_int64(uint64_t a, uint64_t b) { - return ~(a^b); -} - - -static inline uint32_t fill_bit_int32(char src) { - if (src == 0) return 0x00000000; - else return 0xFFFFFFFF; -} - -static inline uint64_t fill_bit_int64(char src) { - if (src == 0) return 0x0000000000000000; - else return 0xFFFFFFFFFFFFFFFF; -} - -void binary_int32_printf(uint32_t src) { - int i; - for (i = 0; i < 32; ++i) { - if (src & 1) printf("1"); - else printf("0"); - src = src >> 1; - } - printf("\n"); -} - -void binary_int64_printf(uint64_t src) { - int i; - for (i = 0; i < 64; ++i) { - if (src & 1) printf("1"); - else printf("0"); - src = src >> 1; - } - printf("\n"); -} - -/* -void gemm_nn_custom_bin_mean(int M, int N, int K, float ALPHA_UNUSED, - unsigned char *A, int lda, - unsigned char *B, int ldb, - float *C, int ldc, float *mean_arr) -{ - int *count_arr = calloc(M*N, sizeof(int)); - - int i, j, k; - for (i = 0; i < M; ++i) { // l.n - filters [16 - 55 - 1024] - for (k = 0; k < K; ++k) { // l.size*l.size*l.c - one filter size [27 - 9216] - char a_bit = get_bit(A, i*lda + k); - - for (j = 0; j < N; ++j) { // out_h*out_w - one channel output size [169 - 173056] - char b_bit = get_bit(B, k*ldb + j); - count_arr[i*ldc + j] += xnor(a_bit, b_bit); - } - } - } - - for (i = 0; i < M; ++i) { - float mean_val = mean_arr[i]; - for (j = 0; j < N; ++j) { - C[i*ldc + j] = (2 * count_arr[i*ldc + j] - K) * mean_val; - } - } - free(count_arr); -} -*/ - -/* -void gemm_nn_custom_bin_mean_transposed(int M, int N, int K, float ALPHA_UNUSED, - unsigned char *A, int lda, - unsigned char *B, int ldb, - float *C, int ldc, float *mean_arr) -{ - int *count_arr = calloc(M*N, sizeof(int)); - - int i, j, k; - for (i = 0; i < M; ++i) { // l.n - filters [16 - 55 - 1024] - for (j = 0; j < N; ++j) { // out_h*out_w - one channel output size [169 - 173056] - for (k = 0; k < K; ++k) { // l.size*l.size*l.c - one filter size [27 - 9216] - char a_bit = get_bit(A, i*lda + k); - char b_bit = get_bit(B, j*ldb + k); - count_arr[i*ldc + j] += xnor(a_bit, b_bit); - } - } - } - - for (i = 0; i < M; ++i) { - float mean_val = mean_arr[i]; - for (j = 0; j < N; ++j) { - C[i*ldc + j] = (2 * count_arr[i*ldc + j] - K) * mean_val; - } - } - free(count_arr); -} -*/ - -/* -void gemm_nn_custom_bin_mean(int M, int N, int K, float ALPHA_UNUSED, - unsigned char *A, int lda, - unsigned char *B, int ldb, - float *C, int ldc, float *mean_arr) -{ - int *count_arr = calloc(M*N, sizeof(int)); - - int i, j, k, h; - -#pragma omp parallel for - for (i = 0; i < M; ++i) { // l.n - filters [16 - 55 - 1024] - for (k = 0; k < K; ++k) { // l.size*l.size*l.c - one filter size [27 - 9216] - const char a_bit = get_bit(A, i*lda + k); - uint64_t a_bit64 = fill_bit_int64(a_bit); - int k_ldb = k*ldb; - - for (j = 0; j < N; j += 64) { // out_h*out_w - one channel output size [169 - 173056] - if ((N - j > 64) && (k_ldb % 8 == 0)) { - uint64_t b_bit64 = *((uint64_t *)(B + (k_ldb + j) / 8)); - uint64_t c_bit64 = xnor_int64(a_bit64, b_bit64); - //printf("\n %d \n",__builtin_popcountll(c_bit64)); // gcc - printf("\n %d \n", __popcnt64(c_bit64)); // msvs - - int h; - for (h = 0; h < 64; ++h) - if ((c_bit64 >> h) & 1) count_arr[i*ldc + j + h] += 1; - - //binary_int64_printf(a_bit64); - //binary_int64_printf(b_bit64); - //binary_int64_printf(c_bit64); - } - else { - for (; j < N; ++j) { // out_h*out_w - one channel output size [169 - 173056] - char b_bit = get_bit(B, k_ldb + j); - if (xnor(a_bit, b_bit)) count_arr[i*ldc + j] += 1; - } - } - - } - } - } - - if (mean_arr) { - //int K_2 = K / 2; - for (i = 0; i < M; ++i) { - float mean_val = mean_arr[i]; - //float mean_val2 = 2 * mean_val; - for (j = 0; j < N; ++j) { - C[i*ldc + j] = (2 * count_arr[i*ldc + j] - K) * mean_val; - //C[i*ldc + j] = (count_arr[i*ldc + j] - K_2) *mean_val2; - } - } - } - else { - for (i = 0; i < M; ++i) { - for (j = 0; j < N; ++j) { - C[i*ldc + j] = count_arr[i*ldc + j] - K / 2; - } - } - } - - free(count_arr); - - //getchar(); -} -*/ - - -/* -void gemm_nn_custom_bin_mean_transposed(int M, int N, int K, float ALPHA_UNUSED, - unsigned char *A, int lda, - unsigned char *B, int ldb, - float *C, int ldc, float *mean_arr) -{ - int i, j, k, h; - -#pragma omp parallel for - for (i = 0; i < M; ++i) { // l.n - filters [16 - 55 - 1024] - float mean_val = mean_arr[i]; - - for (j = 0; j < N; ++j) { // out_h*out_w - one channel output size [169 - 173056] - int count = 0; - - for (k = 0; k < K; k += 64) { // l.size*l.size*l.c - one filter size [27 - 9216] - uint64_t a_bit64 = *((uint64_t *)(A + (i*lda + k) / 8)); - uint64_t b_bit64 = *((uint64_t *)(B + (j*ldb + k) / 8)); - uint64_t c_bit64 = xnor_int64(a_bit64, b_bit64); - -#ifdef WIN32 - int tmp_count = __popcnt64(c_bit64); -#else - int tmp_count = __builtin_popcountll(c_bit64); -#endif - - if (K - k < 64) tmp_count = tmp_count - (64 - (K - k)); // remove extra bits - count += tmp_count; - //binary_int64_printf(c_bit64); - //printf(", count = %d \n\n", tmp_count); - } - - C[i*ldc + j] = (2 * count - K) * mean_val; - } - } -} -*/ - -//---------------------------- - - -#if (defined(__AVX__) && defined(__x86_64__)) || defined(_WIN64) - -#define OSXSAVEFlag (1UL<<27) -#define AVXFlag ((1UL<<28)|OSXSAVEFlag) -#define FMAFlag ((1UL<<12)|AVXFlag|OSXSAVEFlag) -#define CLMULFlag ((1UL<< 1)|AVXFlag|OSXSAVEFlag) -#define VAESFlag ((1UL<<25)|AVXFlag|OSXSAVEFlag) - -#ifdef _WIN64 -#include -#include -#include -#include - -#else // Linux GCC/Clang -#include -#include -#include -#include -#include - -void asm_cpuid(uint32_t* abcd, uint32_t eax) -{ - uint32_t ebx = 0, edx = 0, ecx = 0; - - // EBX is saved to EDI and later restored - __asm__("movl %%ebx, %%edi;" - "cpuid;" - "xchgl %%ebx, %%edi;" - : "=D"(ebx), - "+a"(eax), "+c"(ecx), "=d"(edx)); - - abcd[0] = eax; - abcd[1] = ebx; - abcd[2] = ecx; - abcd[3] = edx; -} - -#endif - -int simd_detect_x86(unsigned int idFeature) -{ - uint32_t regs[4]; // EAX, EBX, ECX, EDX; -#ifdef _WIN32 - __cpuid(regs, 0); - if (regs[0] > 1U) __cpuid(regs, 1); -#else - __get_cpuid(0, ®s[0], ®s[1], ®s[2], ®s[3]); - if(regs[0] > 1U) __get_cpuid(1, ®s[0], ®s[1], ®s[2], ®s[3]); -#endif - - if ((regs[2] & idFeature) != idFeature) - return 0; - return 1; -} - -int is_fma_avx() { - static int result = -1; - if (result == -1) { - result = simd_detect_x86(AVXFlag); - if (result == 1) printf(" Used AVX \n"); - else printf(" Not used AVX \n"); - } - return result; -} - -// https://software.intel.com/sites/landingpage/IntrinsicsGuide -void gemm_nn(int M, int N, int K, float ALPHA, - float *A, int lda, - float *B, int ldb, - float *C, int ldc) -{ - int i, j, k; - if (is_fma_avx() == 1) { // AVX - for (i = 0; i < M; ++i) { - for (k = 0; k < K; ++k) { - float A_PART = ALPHA*A[i*lda + k]; - __m256 a256, b256, c256, result256; // AVX - a256 = _mm256_set1_ps(A_PART); - for (j = 0; j < N - 8; j += 8) { - b256 = _mm256_loadu_ps(&B[k*ldb + j]); - c256 = _mm256_loadu_ps(&C[i*ldc + j]); - // FMA - Intel Haswell (2013), AMD Piledriver (2012) - //result256 = _mm256_fmadd_ps(a256, b256, c256); - result256 = _mm256_mul_ps(a256, b256); - result256 = _mm256_add_ps(result256, c256); - _mm256_storeu_ps(&C[i*ldc + j], result256); - } - - int prev_end = (N % 8 == 0) ? (N - 8) : (N / 8) * 8; - for (j = prev_end; j < N; ++j) - C[i*ldc + j] += A_PART*B[k*ldb + j]; - } - } - } - else { - for (i = 0; i < M; ++i) { - for (k = 0; k < K; ++k) { - register float A_PART = ALPHA*A[i*lda + k]; - for (j = 0; j < N; ++j) { - C[i*ldc + j] += A_PART*B[k*ldb + j]; - } - /* // SSE - __m128 a128, b128, c128, result128; // SSE - a128 = _mm_set1_ps(A_PART); - for (j = 0; j < N - 4; j += 4) { - b128 = _mm_loadu_ps(&B[k*ldb + j]); - c128 = _mm_loadu_ps(&C[i*ldc + j]); - //result128 = _mm_fmadd_ps(a128, b128, c128); - result128 = _mm_mul_ps(a128, b128); - result128 = _mm_add_ps(result128, c128); - _mm_storeu_ps(&C[i*ldc + j], result128); - } - - int prev_end = (N % 4 == 0) ? (N - 4) : (N / 4) * 4; - for (j = prev_end; j < N; ++j){ - C[i*ldc + j] += A_PART*B[k*ldb + j]; - } - */ - } - } - } -} - - -// http://graphics.stanford.edu/~seander/bithacks.html -// https://stackoverflow.com/questions/17354971/fast-counting-the-number-of-set-bits-in-m128i-register -// https://arxiv.org/pdf/1611.07612.pdf - -static inline int popcnt128(__m128i n) { - const __m128i n_hi = _mm_unpackhi_epi64(n, n); -#ifdef _MSC_VER - return __popcnt64(_mm_cvtsi128_si64(n)) + __popcnt64(_mm_cvtsi128_si64(n_hi)); -#else - return __popcntq(_mm_cvtsi128_si64(n)) + __popcntq(_mm_cvtsi128_si64(n_hi)); -#endif -} - -static inline int popcnt256(__m256i n) { - return popcnt128(_mm256_extractf128_si256(n, 0)) + popcnt128(_mm256_extractf128_si256(n, 1)); -} - -static inline __m256i count256(__m256i v) { - __m256i lookup = - _mm256_setr_epi8(0, 1, 1, 2, 1, 2, 2, 3, 1, 2, - 2, 3, 2, 3, 3, 4, 0, 1, 1, 2, 1, 2, 2, 3, - 1, 2, 2, 3, 2, 3, 3, 4); - - __m256i low_mask = _mm256_set1_epi8(0x0f); - - __m256i lo = _mm256_and_si256(v, low_mask); - __m256i hi = _mm256_and_si256(_mm256_srli_epi32(v, 4), low_mask); - __m256i popcnt1 = _mm256_shuffle_epi8(lookup, lo); - __m256i popcnt2 = _mm256_shuffle_epi8(lookup, hi); - __m256i total = _mm256_add_epi8(popcnt1, popcnt2); - - return _mm256_sad_epu8(total, _mm256_setzero_si256()); -} -static inline int popcnt256_custom(__m256i n) { - __m256i val = count256(n); - - return val.m256i_i64[0] + - val.m256i_i64[1] + - val.m256i_i64[2] + - val.m256i_i64[3]; -} - -void gemm_nn_custom_bin_mean_transposed(int M, int N, int K, float ALPHA_UNUSED, - unsigned char *A, int lda, - unsigned char *B, int ldb, - float *C, int ldc, float *mean_arr) -{ - int i; - - static int max_num_threads = 0; - if (max_num_threads == 0) { - max_num_threads = omp_get_max_threads(); - omp_set_num_threads(max_num_threads / 2); - } - - #pragma omp parallel for - for (i = 0; i < M; ++i) - { // l.n - filters [16 - 55 - 1024] - float mean_val = mean_arr[i]; - int j, k; - __m256i all_1 = _mm256_set1_epi8(255); - - for (j = 0; j < N; ++j) { // out_h*out_w - one channel output size [169 - 173056] - int count = 0; - const int bit_step = 256; - __m256i count_sum = _mm256_set1_epi8(0); - - for (k = 0; k < K; k += bit_step) { // l.size*l.size*l.c - one filter size [27 - 9216] - __m256i a_bit256 = _mm256_loadu_si256((__m256i *)(A + (i*lda + k) / 8)); - __m256i b_bit256 = _mm256_loadu_si256((__m256i *)(B + (j*ldb + k) / 8)); - __m256i xor256 = _mm256_xor_si256(a_bit256, b_bit256); // xnor = not(xor(a,b)) - __m256i c_bit256 = _mm256_andnot_si256(xor256, all_1); // can be optimized - we can do other NOT for wegihts once and do not do this NOT - - count_sum = _mm256_add_epi64(count256(c_bit256), count_sum); // Mula’s algorithm - - //count += popcnt256(c_bit256); - - //binary_int64_printf(c_bit64); - //printf(", count = %d \n\n", tmp_count); - } - - // count of 1 bits - count = count_sum.m256i_i64[0] + - count_sum.m256i_i64[1] + - count_sum.m256i_i64[2] + - count_sum.m256i_i64[3]; - - int f1 = (K % bit_step == 0) ? 0 : (bit_step - (K % bit_step)); - count = count - f1; // remove extra bits (from empty space for align only) - - C[i*ldc + j] = (2 * count - K) * mean_val; - } - } -} - - -static inline float im2col_get_pixel(float *im, int height, int width, int channels, - int row, int col, int channel, int pad) -{ - row -= pad; - col -= pad; - - if (row < 0 || col < 0 || - row >= height || col >= width) return 0; - return im[col + width*(row + height*channel)]; -} - -//From Berkeley Vision's Caffe! -//https://github.com/BVLC/caffe/blob/master/LICENSE -void im2col_cpu_custom(float* data_im, - int channels, int height, int width, - int ksize, int stride, int pad, float* data_col) -{ - - int c, h, w; - int height_col = (height + 2 * pad - ksize) / stride + 1; - int width_col = (width + 2 * pad - ksize) / stride + 1; - int channels_col = channels * ksize * ksize; - - // optimized version - if (height_col == height && width_col == width && stride == 1 && pad == 1) - { - #pragma omp parallel for - 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 = pad; h < height_col-pad; ++h) { - for (w = pad; w < width_col-pad-8; w += 8) { - int im_row = h_offset + h - pad; - int im_col = w_offset + w - pad; - int col_index = (c * height_col + h) * width_col + w; - - //data_col[col_index] = data_im[im_col + width*(im_row + height*c_im)]; - __m256 src256 = _mm256_loadu_ps((__m256i *)(&data_im[im_col + width*(im_row + height*c_im)])); - _mm256_storeu_ps(&data_col[col_index], src256); - } - - for (; w < width_col - pad; ++w) { - int im_row = h_offset + h - pad; - int im_col = w_offset + w - pad; - int col_index = (c * height_col + h) * width_col + w; - - data_col[col_index] = data_im[im_col + width*(im_row + height*c_im)]; - } - } - - { - w = 0; - for (h = 0; h < height_col; ++h) { - int im_row = h_offset + h; - int im_col = w_offset + w; - int col_index = (c * height_col + h) * width_col + w; - data_col[col_index] = im2col_get_pixel(data_im, height, width, channels, - im_row, im_col, c_im, pad); - } - } - - { - w = width_col-1; - for (h = 0; h < height_col; ++h) { - int im_row = h_offset + h; - int im_col = w_offset + w; - int col_index = (c * height_col + h) * width_col + w; - data_col[col_index] = im2col_get_pixel(data_im, height, width, channels, - im_row, im_col, c_im, pad); - } - } - - { - h = 0; - for (w = 0; w < width_col; ++w) { - int im_row = h_offset + h; - int im_col = w_offset + w; - int col_index = (c * height_col + h) * width_col + w; - data_col[col_index] = im2col_get_pixel(data_im, height, width, channels, - im_row, im_col, c_im, pad); - } - } - - { - h = height_col-1; - for (w = 0; w < width_col; ++w) { - int im_row = h_offset + h; - int im_col = w_offset + w; - int col_index = (c * height_col + h) * width_col + w; - data_col[col_index] = im2col_get_pixel(data_im, height, width, channels, - im_row, im_col, c_im, pad); - } - } - } - - } - else { - //printf("\n Error: is no non-optimized version \n"); - im2col_cpu(data_im, channels, height, width, ksize, stride, pad, data_col); - } -} - -void activate_array_cpu_custom(float *x, const int n, const ACTIVATION a) -{ - int i; - if (a == LINEAR) - {} - else if (a == LEAKY) - { - __m256i all256_sing1 = _mm256_set_epi32(0x80000000, 0x80000000, 0x80000000, 0x80000000, 0x80000000, 0x80000000, 0x80000000, 0x80000000); - __m256 all256_01 = _mm256_set1_ps(0.1F); - - for (i = 0; i < n; i += 8) { - //x[i] = (x[i]>0) ? x[i] : .1*x[i]; - - __m256 src256 = _mm256_loadu_ps((__m256 *)(&x[i])); - __m256 mult256 = _mm256_mul_ps((src256), all256_01); // mult * 0.1 - - __m256i sign256 = _mm256_and_si256(_mm256_castps_si256(src256), all256_sing1); // check sign in 8 x 32-bit floats - - __m256 result256 = _mm256_blendv_ps(src256, mult256, _mm256_castsi256_ps(sign256)); // (sign>0) ? src : mult; - _mm256_storeu_ps((__m256 *)(&x[i]), result256); - } - - for (; i < n; ++i) { - x[i] = (x[i]>0) ? x[i] : .1*x[i]; - } - } - else { - for (i = 0; i < n; ++i) { - x[i] = activate(x[i], a); - } - } -} - -void float_to_bit(float *src, unsigned char *dst, size_t size) -{ - size_t dst_size = size / 8 + 1; - memset(dst, 0, dst_size); - - size_t i; - __m256i all256_sing1 = _mm256_set_epi32(0x80000000, 0x80000000, 0x80000000, 0x80000000, 0x80000000, 0x80000000, 0x80000000, 0x80000000); - - for (i = 0; i < size; i+=8) - { - __m256i src256 = _mm256_loadu_si256((__m256i *)(&src[i])); - __m256i result256 = _mm256_and_si256(src256, all256_sing1); // check sign in 8 x 32-bit floats - - uint32_t mask = _mm256_movemask_ps(_mm256_castsi256_ps(result256)); // (val >= 0) ? 0 : 1 - mask = ~mask; // inverse mask, (val >= 0) ? 1 : 0 - - dst[i / 8] = mask; - } -} - -static inline void transpose4x4_SSE(float *A, float *B, const int lda, const int ldb) -{ - __m128 row1 = _mm_load_ps(&A[0 * lda]); - __m128 row2 = _mm_load_ps(&A[1 * lda]); - __m128 row3 = _mm_load_ps(&A[2 * lda]); - __m128 row4 = _mm_load_ps(&A[3 * lda]); - _MM_TRANSPOSE4_PS(row1, row2, row3, row4); - _mm_store_ps(&B[0 * ldb], row1); - _mm_store_ps(&B[1 * ldb], row2); - _mm_store_ps(&B[2 * ldb], row3); - _mm_store_ps(&B[3 * ldb], row4); -} - -void transpose_block_SSE4x4(float *A, float *B, const int n, const int m, - const int lda, const int ldb, const int block_size) -{ - int i; - if (block_size % 4 == 0) { - #pragma omp parallel for - for (i = 0; i < n; i += block_size) { - int j, i2, j2; - for (j = 0; j < m; j += block_size) { - int max_i2 = i + block_size < n ? i + block_size : n; - int max_j2 = j + block_size < m ? j + block_size : m; - for (i2 = i; i2 < max_i2; i2 += 4) { - for (j2 = j; j2 < max_j2; j2 += 4) { - transpose4x4_SSE(&A[i2*lda + j2], &B[j2*ldb + i2], lda, ldb); - } - } - } - } - } - else { - #pragma omp parallel for - for (i = 0; i < n; i += block_size) { - int j, i2, j2; - for (j = 0; j < m; j += block_size) { - int max_i2 = i + block_size < n ? i + block_size : n; - int max_j2 = j + block_size < m ? j + block_size : m; - for (i2 = i; i2 < max_i2; ++i2) { - for (j2 = j; j2 < max_j2; ++j2) { - B[j2*ldb + i2] = A[i2*lda + j2]; - } - } - } - } - } -} - - -#else - -void gemm_nn(int M, int N, int K, float ALPHA, - float *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) { - register float A_PART = ALPHA*A[i*lda + k]; - for (j = 0; j < N; ++j) { - C[i*ldc + j] += A_PART*B[k*ldb + j]; - } - } - } -} - -void gemm_nn_custom_bin_mean_transposed(int M, int N, int K, float ALPHA_UNUSED, - unsigned char *A, int lda, - unsigned char *B, int ldb, - float *C, int ldc, float *mean_arr) -{ - int i, j, k, h; - -#pragma omp parallel for - for (i = 0; i < M; ++i) { // l.n - filters [16 - 55 - 1024] - float mean_val = mean_arr[i]; - - for (j = 0; j < N; ++j) { // out_h*out_w - one channel output size [169 - 173056] - int count = 0; - - for (k = 0; k < K; k += 64) { // l.size*l.size*l.c - one filter size [27 - 9216] - uint64_t a_bit64 = *((uint64_t *)(A + (i*lda + k) / 8)); - uint64_t b_bit64 = *((uint64_t *)(B + (j*ldb + k) / 8)); - uint64_t c_bit64 = xnor_int64(a_bit64, b_bit64); - -#ifdef WIN32 - int tmp_count = __popcnt64(c_bit64); -#else - int tmp_count = __builtin_popcountll(c_bit64); -#endif - - if (K - k < 64) tmp_count = tmp_count - (64 - (K - k)); // remove extra bits - count += tmp_count; - //binary_int64_printf(c_bit64); - //printf(", count = %d \n\n", tmp_count); - } - - C[i*ldc + j] = (2 * count - K) * mean_val; - } - } -} - -//From Berkeley Vision's Caffe! -//https://github.com/BVLC/caffe/blob/master/LICENSE -void im2col_cpu_custom(float* data_im, - int channels, int height, int width, - int ksize, int stride, int pad, float* data_col) -{ - - int c, h, w; - int height_col = (height + 2 * pad - ksize) / stride + 1; - int width_col = (width + 2 * pad - ksize) / stride + 1; - int channels_col = channels * ksize * ksize; - - // optimized version - if (height_col == height && width_col == width && stride == 1 && pad == 1) - { - #pragma omp parallel for - 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 = pad; h < height_col - pad; ++h) { - for (w = pad; w < width_col - pad; ++w) { - int im_row = h_offset + h - pad; - int im_col = w_offset + w - pad; - int col_index = (c * height_col + h) * width_col + w; - - data_col[col_index] = data_im[im_col + width*(im_row + height*c_im)]; - } - - for (; w < width_col - pad; ++w) { - int im_row = h_offset + h - pad; - int im_col = w_offset + w - pad; - int col_index = (c * height_col + h) * width_col + w; - - data_col[col_index] = data_im[im_col + width*(im_row + height*c_im)]; - } -} - - { - w = 0; - for (h = 0; h < height_col; ++h) { - int im_row = h_offset + h; - int im_col = w_offset + w; - int col_index = (c * height_col + h) * width_col + w; - data_col[col_index] = im2col_get_pixel(data_im, height, width, channels, - im_row, im_col, c_im, pad); - } - } - - { - w = width_col - 1; - for (h = 0; h < height_col; ++h) { - int im_row = h_offset + h; - int im_col = w_offset + w; - int col_index = (c * height_col + h) * width_col + w; - data_col[col_index] = im2col_get_pixel(data_im, height, width, channels, - im_row, im_col, c_im, pad); - } - } - - { - h = 0; - for (w = 0; w < width_col; ++w) { - int im_row = h_offset + h; - int im_col = w_offset + w; - int col_index = (c * height_col + h) * width_col + w; - data_col[col_index] = im2col_get_pixel(data_im, height, width, channels, - im_row, im_col, c_im, pad); - } - } - - { - h = height_col - 1; - for (w = 0; w < width_col; ++w) { - int im_row = h_offset + h; - int im_col = w_offset + w; - int col_index = (c * height_col + h) * width_col + w; - data_col[col_index] = im2col_get_pixel(data_im, height, width, channels, - im_row, im_col, c_im, pad); - } - } - } - - } - else { - //printf("\n Error: is no non-optimized version \n"); - im2col_cpu(data_im, channels, height, width, ksize, stride, pad, data_col); - } -} - -void activate_array_cpu_custom(float *x, const int n, const ACTIVATION a) -{ - int i; - if (a == LINEAR) - { - } - else if (a == LEAKY) - { - for (i = 0; i < n; ++i) { - x[i] = (x[i]>0) ? x[i] : .1*x[i]; - } - } - else { - for (i = 0; i < n; ++i) { - x[i] = activate(x[i], a); - } - } -} - -void float_to_bit(float *src, unsigned char *dst, size_t size) -{ - size_t dst_size = size / 8 + 1; - memset(dst, 0, dst_size); - - size_t i; - char *byte_arr = calloc(size, sizeof(char)); - for (i = 0; i < size; ++i) { - if (src[i] > 0) byte_arr[i] = 1; - } - - //for (i = 0; i < size; ++i) { - // dst[i / 8] |= byte_arr[i] << (i % 8); - //} - - for (i = 0; i < size; i += 8) { - char dst_tmp = 0; - dst_tmp |= byte_arr[i + 0] << 0; - dst_tmp |= byte_arr[i + 1] << 1; - dst_tmp |= byte_arr[i + 2] << 2; - dst_tmp |= byte_arr[i + 3] << 3; - dst_tmp |= byte_arr[i + 4] << 4; - dst_tmp |= byte_arr[i + 5] << 5; - dst_tmp |= byte_arr[i + 6] << 6; - dst_tmp |= byte_arr[i + 7] << 7; - dst[i / 8] = dst_tmp; - } - free(byte_arr); -} - -static inline void transpose_scalar_block(float *A, float *B, const int lda, const int ldb, const int block_size) -{ - int i, j; - //#pragma omp parallel for - for (i = 0; i - -void gemm_ongpu(int TA, int TB, int M, int N, int K, float ALPHA, - float *A_gpu, int lda, - float *B_gpu, int ldb, - float BETA, - float *C_gpu, int 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_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) -{ - 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); - - cuda_pull_array(C_gpu, C, ldc*M); - cuda_free(A_gpu); - cuda_free(B_gpu); - cuda_free(C_gpu); -} - -#include -#include -#include -#include - -void time_gpu_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<32; ++i){ - gemm_gpu(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 s\n",m,k,k,n, TA, TB, (float)(end-start)/CLOCKS_PER_SEC); - free(a); - free(b); - free(c); -} - -void time_ongpu(int TA, int TB, int m, int k, int n) -{ - int iter = 10; - float *a = random_matrix(m,k); - float *b = random_matrix(k,n); - - int lda = (!TA)?k:m; - int ldb = (!TB)?n:k; - - float *c = random_matrix(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 +#include +#include + +#if defined(_OPENMP) +#include +#endif + +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, + float *B, int ldb, + float BETA, + float *C, int ldc) +{ + gemm_cpu( TA, TB, M, N, K, ALPHA,A,lda, B, ldb,BETA,C,ldc); +} + + +//-------------------------------------------- +// XNOR bitwise GEMM for binary neural network +//-------------------------------------------- + +#include + +static inline unsigned char xnor(unsigned char a, unsigned char b) { + //return a == b; + return !(a^b); +} + +// INT-32 +static inline uint32_t get_bit_int32(uint32_t const*const src, size_t index) { + size_t src_i = index / 32; + int src_shift = index % 32; + unsigned char val = (src[src_i] & (1 << src_shift)) > 0; + return val; +} + +static inline uint32_t xnor_int32(uint32_t a, uint32_t b) { + return ~(a^b); +} + +static inline uint64_t xnor_int64(uint64_t a, uint64_t b) { + return ~(a^b); +} + + +static inline uint32_t fill_bit_int32(char src) { + if (src == 0) return 0x00000000; + else return 0xFFFFFFFF; +} + +static inline uint64_t fill_bit_int64(char src) { + if (src == 0) return 0x0000000000000000; + else return 0xFFFFFFFFFFFFFFFF; +} + +void binary_int32_printf(uint32_t src) { + int i; + for (i = 0; i < 32; ++i) { + if (src & 1) printf("1"); + else printf("0"); + src = src >> 1; + } + printf("\n"); +} + +void binary_int64_printf(uint64_t src) { + int i; + for (i = 0; i < 64; ++i) { + if (src & 1) printf("1"); + else printf("0"); + src = src >> 1; + } + printf("\n"); +} + +/* +void gemm_nn_custom_bin_mean(int M, int N, int K, float ALPHA_UNUSED, + unsigned char *A, int lda, + unsigned char *B, int ldb, + float *C, int ldc, float *mean_arr) +{ + int *count_arr = calloc(M*N, sizeof(int)); + + int i, j, k; + for (i = 0; i < M; ++i) { // l.n - filters [16 - 55 - 1024] + for (k = 0; k < K; ++k) { // l.size*l.size*l.c - one filter size [27 - 9216] + char a_bit = get_bit(A, i*lda + k); + + for (j = 0; j < N; ++j) { // out_h*out_w - one channel output size [169 - 173056] + char b_bit = get_bit(B, k*ldb + j); + count_arr[i*ldc + j] += xnor(a_bit, b_bit); + } + } + } + + for (i = 0; i < M; ++i) { + float mean_val = mean_arr[i]; + for (j = 0; j < N; ++j) { + C[i*ldc + j] = (2 * count_arr[i*ldc + j] - K) * mean_val; + } + } + free(count_arr); +} +*/ + +/* +void gemm_nn_custom_bin_mean_transposed(int M, int N, int K, float ALPHA_UNUSED, + unsigned char *A, int lda, + unsigned char *B, int ldb, + float *C, int ldc, float *mean_arr) +{ + int *count_arr = calloc(M*N, sizeof(int)); + + int i, j, k; + for (i = 0; i < M; ++i) { // l.n - filters [16 - 55 - 1024] + for (j = 0; j < N; ++j) { // out_h*out_w - one channel output size [169 - 173056] + for (k = 0; k < K; ++k) { // l.size*l.size*l.c - one filter size [27 - 9216] + char a_bit = get_bit(A, i*lda + k); + char b_bit = get_bit(B, j*ldb + k); + count_arr[i*ldc + j] += xnor(a_bit, b_bit); + } + } + } + + for (i = 0; i < M; ++i) { + float mean_val = mean_arr[i]; + for (j = 0; j < N; ++j) { + C[i*ldc + j] = (2 * count_arr[i*ldc + j] - K) * mean_val; + } + } + free(count_arr); +} +*/ + +/* +void gemm_nn_custom_bin_mean(int M, int N, int K, float ALPHA_UNUSED, + unsigned char *A, int lda, + unsigned char *B, int ldb, + float *C, int ldc, float *mean_arr) +{ + int *count_arr = calloc(M*N, sizeof(int)); + + int i, j, k, h; + +#pragma omp parallel for + for (i = 0; i < M; ++i) { // l.n - filters [16 - 55 - 1024] + for (k = 0; k < K; ++k) { // l.size*l.size*l.c - one filter size [27 - 9216] + const char a_bit = get_bit(A, i*lda + k); + uint64_t a_bit64 = fill_bit_int64(a_bit); + int k_ldb = k*ldb; + + for (j = 0; j < N; j += 64) { // out_h*out_w - one channel output size [169 - 173056] + if ((N - j > 64) && (k_ldb % 8 == 0)) { + uint64_t b_bit64 = *((uint64_t *)(B + (k_ldb + j) / 8)); + uint64_t c_bit64 = xnor_int64(a_bit64, b_bit64); + //printf("\n %d \n",__builtin_popcountll(c_bit64)); // gcc + printf("\n %d \n", __popcnt64(c_bit64)); // msvs + + int h; + for (h = 0; h < 64; ++h) + if ((c_bit64 >> h) & 1) count_arr[i*ldc + j + h] += 1; + + //binary_int64_printf(a_bit64); + //binary_int64_printf(b_bit64); + //binary_int64_printf(c_bit64); + } + else { + for (; j < N; ++j) { // out_h*out_w - one channel output size [169 - 173056] + char b_bit = get_bit(B, k_ldb + j); + if (xnor(a_bit, b_bit)) count_arr[i*ldc + j] += 1; + } + } + + } + } + } + + if (mean_arr) { + //int K_2 = K / 2; + for (i = 0; i < M; ++i) { + float mean_val = mean_arr[i]; + //float mean_val2 = 2 * mean_val; + for (j = 0; j < N; ++j) { + C[i*ldc + j] = (2 * count_arr[i*ldc + j] - K) * mean_val; + //C[i*ldc + j] = (count_arr[i*ldc + j] - K_2) *mean_val2; + } + } + } + else { + for (i = 0; i < M; ++i) { + for (j = 0; j < N; ++j) { + C[i*ldc + j] = count_arr[i*ldc + j] - K / 2; + } + } + } + + free(count_arr); + + //getchar(); +} +*/ + + +/* +void gemm_nn_custom_bin_mean_transposed(int M, int N, int K, float ALPHA_UNUSED, + unsigned char *A, int lda, + unsigned char *B, int ldb, + float *C, int ldc, float *mean_arr) +{ + int i, j, k, h; + +#pragma omp parallel for + for (i = 0; i < M; ++i) { // l.n - filters [16 - 55 - 1024] + float mean_val = mean_arr[i]; + + for (j = 0; j < N; ++j) { // out_h*out_w - one channel output size [169 - 173056] + int count = 0; + + for (k = 0; k < K; k += 64) { // l.size*l.size*l.c - one filter size [27 - 9216] + uint64_t a_bit64 = *((uint64_t *)(A + (i*lda + k) / 8)); + uint64_t b_bit64 = *((uint64_t *)(B + (j*ldb + k) / 8)); + uint64_t c_bit64 = xnor_int64(a_bit64, b_bit64); + +#ifdef WIN32 + int tmp_count = __popcnt64(c_bit64); +#else + int tmp_count = __builtin_popcountll(c_bit64); +#endif + + if (K - k < 64) tmp_count = tmp_count - (64 - (K - k)); // remove extra bits + count += tmp_count; + //binary_int64_printf(c_bit64); + //printf(", count = %d \n\n", tmp_count); + } + + C[i*ldc + j] = (2 * count - K) * mean_val; + } + } +} +*/ + +//---------------------------- + + +#if (defined(__AVX__) && defined(__x86_64__)) || defined(_WIN64) + +#define OSXSAVEFlag (1UL<<27) +#define AVXFlag ((1UL<<28)|OSXSAVEFlag) +#define FMAFlag ((1UL<<12)|AVXFlag|OSXSAVEFlag) +#define CLMULFlag ((1UL<< 1)|AVXFlag|OSXSAVEFlag) +#define VAESFlag ((1UL<<25)|AVXFlag|OSXSAVEFlag) + +#ifdef _WIN64 +#include +#include +#include +#include + +#else // Linux GCC/Clang +#include +#include +#include +#include +#include + +void asm_cpuid(uint32_t* abcd, uint32_t eax) +{ + uint32_t ebx = 0, edx = 0, ecx = 0; + + // EBX is saved to EDI and later restored + __asm__("movl %%ebx, %%edi;" + "cpuid;" + "xchgl %%ebx, %%edi;" + : "=D"(ebx), + "+a"(eax), "+c"(ecx), "=d"(edx)); + + abcd[0] = eax; + abcd[1] = ebx; + abcd[2] = ecx; + abcd[3] = edx; +} + +#endif + +int simd_detect_x86(unsigned int idFeature) +{ + uint32_t regs[4]; // EAX, EBX, ECX, EDX; +#ifdef _WIN32 + __cpuid(regs, 0); + if (regs[0] > 1U) __cpuid(regs, 1); +#else + __get_cpuid(0, ®s[0], ®s[1], ®s[2], ®s[3]); + if(regs[0] > 1U) __get_cpuid(1, ®s[0], ®s[1], ®s[2], ®s[3]); +#endif + + if ((regs[2] & idFeature) != idFeature) + return 0; + return 1; +} + +int is_fma_avx() { + static int result = -1; + if (result == -1) { + result = simd_detect_x86(AVXFlag); + if (result == 1) printf(" Used AVX \n"); + else printf(" Not used AVX \n"); + } + return result; +} + +// https://software.intel.com/sites/landingpage/IntrinsicsGuide +void gemm_nn(int M, int N, int K, float ALPHA, + float *A, int lda, + float *B, int ldb, + float *C, int ldc) +{ + int i, j, k; + if (is_fma_avx() == 1) { // AVX + for (i = 0; i < M; ++i) { + for (k = 0; k < K; ++k) { + float A_PART = ALPHA*A[i*lda + k]; + __m256 a256, b256, c256, result256; // AVX + a256 = _mm256_set1_ps(A_PART); + for (j = 0; j < N - 8; j += 8) { + b256 = _mm256_loadu_ps(&B[k*ldb + j]); + c256 = _mm256_loadu_ps(&C[i*ldc + j]); + // FMA - Intel Haswell (2013), AMD Piledriver (2012) + //result256 = _mm256_fmadd_ps(a256, b256, c256); + result256 = _mm256_mul_ps(a256, b256); + result256 = _mm256_add_ps(result256, c256); + _mm256_storeu_ps(&C[i*ldc + j], result256); + } + + int prev_end = (N % 8 == 0) ? (N - 8) : (N / 8) * 8; + for (j = prev_end; j < N; ++j) + C[i*ldc + j] += A_PART*B[k*ldb + j]; + } + } + } + else { + for (i = 0; i < M; ++i) { + for (k = 0; k < K; ++k) { + register float A_PART = ALPHA*A[i*lda + k]; + for (j = 0; j < N; ++j) { + C[i*ldc + j] += A_PART*B[k*ldb + j]; + } + /* // SSE + __m128 a128, b128, c128, result128; // SSE + a128 = _mm_set1_ps(A_PART); + for (j = 0; j < N - 4; j += 4) { + b128 = _mm_loadu_ps(&B[k*ldb + j]); + c128 = _mm_loadu_ps(&C[i*ldc + j]); + //result128 = _mm_fmadd_ps(a128, b128, c128); + result128 = _mm_mul_ps(a128, b128); + result128 = _mm_add_ps(result128, c128); + _mm_storeu_ps(&C[i*ldc + j], result128); + } + + int prev_end = (N % 4 == 0) ? (N - 4) : (N / 4) * 4; + for (j = prev_end; j < N; ++j){ + C[i*ldc + j] += A_PART*B[k*ldb + j]; + } + */ + } + } + } +} + + +// http://graphics.stanford.edu/~seander/bithacks.html +// https://stackoverflow.com/questions/17354971/fast-counting-the-number-of-set-bits-in-m128i-register +// https://arxiv.org/pdf/1611.07612.pdf + +static inline int popcnt128(__m128i n) { + const __m128i n_hi = _mm_unpackhi_epi64(n, n); +#ifdef _MSC_VER + return __popcnt64(_mm_cvtsi128_si64(n)) + __popcnt64(_mm_cvtsi128_si64(n_hi)); +#else + return __popcntq(_mm_cvtsi128_si64(n)) + __popcntq(_mm_cvtsi128_si64(n_hi)); +#endif +} + +static inline int popcnt256(__m256i n) { + return popcnt128(_mm256_extractf128_si256(n, 0)) + popcnt128(_mm256_extractf128_si256(n, 1)); +} + +static inline __m256i count256(__m256i v) { + __m256i lookup = + _mm256_setr_epi8(0, 1, 1, 2, 1, 2, 2, 3, 1, 2, + 2, 3, 2, 3, 3, 4, 0, 1, 1, 2, 1, 2, 2, 3, + 1, 2, 2, 3, 2, 3, 3, 4); + + __m256i low_mask = _mm256_set1_epi8(0x0f); + + __m256i lo = _mm256_and_si256(v, low_mask); + __m256i hi = _mm256_and_si256(_mm256_srli_epi32(v, 4), low_mask); + __m256i popcnt1 = _mm256_shuffle_epi8(lookup, lo); + __m256i popcnt2 = _mm256_shuffle_epi8(lookup, hi); + __m256i total = _mm256_add_epi8(popcnt1, popcnt2); + + return _mm256_sad_epu8(total, _mm256_setzero_si256()); +} + +static inline int popcnt256_custom(__m256i n) { + __m256i val = count256(n); + + return val.m256i_i64[0] + + val.m256i_i64[1] + + val.m256i_i64[2] + + val.m256i_i64[3]; +} + +void gemm_nn_custom_bin_mean_transposed(int M, int N, int K, float ALPHA_UNUSED, + unsigned char *A, int lda, + unsigned char *B, int ldb, + float *C, int ldc, float *mean_arr) +{ + int i; + +#if defined(_OPENMP) + static int max_num_threads = 0; + if (max_num_threads == 0) { + max_num_threads = omp_get_max_threads(); + omp_set_num_threads(max_num_threads / 2); + } +#endif + + #pragma omp parallel for + for (i = 0; i < M; ++i) + { // l.n - filters [16 - 55 - 1024] + float mean_val = mean_arr[i]; + int j, k; + __m256i all_1 = _mm256_set1_epi8(255); + + for (j = 0; j < N; ++j) { // out_h*out_w - one channel output size [169 - 173056] + int count = 0; + const int bit_step = 256; + __m256i count_sum = _mm256_set1_epi8(0); + + for (k = 0; k < K; k += bit_step) { // l.size*l.size*l.c - one filter size [27 - 9216] + __m256i a_bit256 = _mm256_loadu_si256((__m256i *)(A + (i*lda + k) / 8)); + __m256i b_bit256 = _mm256_loadu_si256((__m256i *)(B + (j*ldb + k) / 8)); + __m256i xor256 = _mm256_xor_si256(a_bit256, b_bit256); // xnor = not(xor(a,b)) + __m256i c_bit256 = _mm256_andnot_si256(xor256, all_1); // can be optimized - we can do other NOT for wegihts once and do not do this NOT + + count_sum = _mm256_add_epi64(count256(c_bit256), count_sum); // Mula’s algorithm + + //count += popcnt256(c_bit256); + + //binary_int64_printf(c_bit64); + //printf(", count = %d \n\n", tmp_count); + } + + // count of 1 bits + count = count_sum.m256i_i64[0] + + count_sum.m256i_i64[1] + + count_sum.m256i_i64[2] + + count_sum.m256i_i64[3]; + + int f1 = (K % bit_step == 0) ? 0 : (bit_step - (K % bit_step)); + count = count - f1; // remove extra bits (from empty space for align only) + + C[i*ldc + j] = (2 * count - K) * mean_val; + } + } +} + + +static inline float im2col_get_pixel(float *im, int height, int width, int channels, + int row, int col, int channel, int pad) +{ + row -= pad; + col -= pad; + + if (row < 0 || col < 0 || + row >= height || col >= width) return 0; + return im[col + width*(row + height*channel)]; +} + +//From Berkeley Vision's Caffe! +//https://github.com/BVLC/caffe/blob/master/LICENSE +void im2col_cpu_custom(float* data_im, + int channels, int height, int width, + int ksize, int stride, int pad, float* data_col) +{ + + int c, h, w; + int height_col = (height + 2 * pad - ksize) / stride + 1; + int width_col = (width + 2 * pad - ksize) / stride + 1; + int channels_col = channels * ksize * ksize; + + // optimized version + if (height_col == height && width_col == width && stride == 1 && pad == 1) + { + #pragma omp parallel for + 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 = pad; h < height_col-pad; ++h) { + for (w = pad; w < width_col-pad-8; w += 8) { + int im_row = h_offset + h - pad; + int im_col = w_offset + w - pad; + int col_index = (c * height_col + h) * width_col + w; + + //data_col[col_index] = data_im[im_col + width*(im_row + height*c_im)]; + __m256 src256 = _mm256_loadu_ps((__m256i *)(&data_im[im_col + width*(im_row + height*c_im)])); + _mm256_storeu_ps(&data_col[col_index], src256); + } + + for (; w < width_col - pad; ++w) { + int im_row = h_offset + h - pad; + int im_col = w_offset + w - pad; + int col_index = (c * height_col + h) * width_col + w; + + data_col[col_index] = data_im[im_col + width*(im_row + height*c_im)]; + } + } + + { + w = 0; + for (h = 0; h < height_col; ++h) { + int im_row = h_offset + h; + int im_col = w_offset + w; + int col_index = (c * height_col + h) * width_col + w; + data_col[col_index] = im2col_get_pixel(data_im, height, width, channels, + im_row, im_col, c_im, pad); + } + } + + { + w = width_col-1; + for (h = 0; h < height_col; ++h) { + int im_row = h_offset + h; + int im_col = w_offset + w; + int col_index = (c * height_col + h) * width_col + w; + data_col[col_index] = im2col_get_pixel(data_im, height, width, channels, + im_row, im_col, c_im, pad); + } + } + + { + h = 0; + for (w = 0; w < width_col; ++w) { + int im_row = h_offset + h; + int im_col = w_offset + w; + int col_index = (c * height_col + h) * width_col + w; + data_col[col_index] = im2col_get_pixel(data_im, height, width, channels, + im_row, im_col, c_im, pad); + } + } + + { + h = height_col-1; + for (w = 0; w < width_col; ++w) { + int im_row = h_offset + h; + int im_col = w_offset + w; + int col_index = (c * height_col + h) * width_col + w; + data_col[col_index] = im2col_get_pixel(data_im, height, width, channels, + im_row, im_col, c_im, pad); + } + } + } + + } + else { + //printf("\n Error: is no non-optimized version \n"); + im2col_cpu(data_im, channels, height, width, ksize, stride, pad, data_col); + } +} + +void activate_array_cpu_custom(float *x, const int n, const ACTIVATION a) +{ + int i; + if (a == LINEAR) + {} + else if (a == LEAKY) + { + __m256i all256_sing1 = _mm256_set_epi32(0x80000000, 0x80000000, 0x80000000, 0x80000000, 0x80000000, 0x80000000, 0x80000000, 0x80000000); + __m256 all256_01 = _mm256_set1_ps(0.1F); + + for (i = 0; i < n; i += 8) { + //x[i] = (x[i]>0) ? x[i] : .1*x[i]; + + __m256 src256 = _mm256_loadu_ps((__m256 *)(&x[i])); + __m256 mult256 = _mm256_mul_ps((src256), all256_01); // mult * 0.1 + + __m256i sign256 = _mm256_and_si256(_mm256_castps_si256(src256), all256_sing1); // check sign in 8 x 32-bit floats + + __m256 result256 = _mm256_blendv_ps(src256, mult256, _mm256_castsi256_ps(sign256)); // (sign>0) ? src : mult; + _mm256_storeu_ps((__m256 *)(&x[i]), result256); + } + + for (; i < n; ++i) { + x[i] = (x[i]>0) ? x[i] : .1*x[i]; + } + } + else { + for (i = 0; i < n; ++i) { + x[i] = activate(x[i], a); + } + } +} + +void float_to_bit(float *src, unsigned char *dst, size_t size) +{ + size_t dst_size = size / 8 + 1; + memset(dst, 0, dst_size); + + size_t i; + __m256i all256_sing1 = _mm256_set_epi32(0x80000000, 0x80000000, 0x80000000, 0x80000000, 0x80000000, 0x80000000, 0x80000000, 0x80000000); + + for (i = 0; i < size; i+=8) + { + __m256i src256 = _mm256_loadu_si256((__m256i *)(&src[i])); + __m256i result256 = _mm256_and_si256(src256, all256_sing1); // check sign in 8 x 32-bit floats + + uint32_t mask = _mm256_movemask_ps(_mm256_castsi256_ps(result256)); // (val >= 0) ? 0 : 1 + mask = ~mask; // inverse mask, (val >= 0) ? 1 : 0 + + dst[i / 8] = mask; + } +} + +static inline void transpose4x4_SSE(float *A, float *B, const int lda, const int ldb) +{ + __m128 row1 = _mm_load_ps(&A[0 * lda]); + __m128 row2 = _mm_load_ps(&A[1 * lda]); + __m128 row3 = _mm_load_ps(&A[2 * lda]); + __m128 row4 = _mm_load_ps(&A[3 * lda]); + _MM_TRANSPOSE4_PS(row1, row2, row3, row4); + _mm_store_ps(&B[0 * ldb], row1); + _mm_store_ps(&B[1 * ldb], row2); + _mm_store_ps(&B[2 * ldb], row3); + _mm_store_ps(&B[3 * ldb], row4); +} + +void transpose_block_SSE4x4(float *A, float *B, const int n, const int m, + const int lda, const int ldb, const int block_size) +{ + int i; + if (block_size % 4 == 0) { + #pragma omp parallel for + for (i = 0; i < n; i += block_size) { + int j, i2, j2; + for (j = 0; j < m; j += block_size) { + int max_i2 = i + block_size < n ? i + block_size : n; + int max_j2 = j + block_size < m ? j + block_size : m; + for (i2 = i; i2 < max_i2; i2 += 4) { + for (j2 = j; j2 < max_j2; j2 += 4) { + transpose4x4_SSE(&A[i2*lda + j2], &B[j2*ldb + i2], lda, ldb); + } + } + } + } + } + else { + #pragma omp parallel for + for (i = 0; i < n; i += block_size) { + int j, i2, j2; + for (j = 0; j < m; j += block_size) { + int max_i2 = i + block_size < n ? i + block_size : n; + int max_j2 = j + block_size < m ? j + block_size : m; + for (i2 = i; i2 < max_i2; ++i2) { + for (j2 = j; j2 < max_j2; ++j2) { + B[j2*ldb + i2] = A[i2*lda + j2]; + } + } + } + } + } +} + + +#else + +void gemm_nn(int M, int N, int K, float ALPHA, + float *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) { + register float A_PART = ALPHA*A[i*lda + k]; + for (j = 0; j < N; ++j) { + C[i*ldc + j] += A_PART*B[k*ldb + j]; + } + } + } +} + +void gemm_nn_custom_bin_mean_transposed(int M, int N, int K, float ALPHA_UNUSED, + unsigned char *A, int lda, + unsigned char *B, int ldb, + float *C, int ldc, float *mean_arr) +{ + int i, j, k, h; + +#pragma omp parallel for + for (i = 0; i < M; ++i) { // l.n - filters [16 - 55 - 1024] + float mean_val = mean_arr[i]; + + for (j = 0; j < N; ++j) { // out_h*out_w - one channel output size [169 - 173056] + int count = 0; + + for (k = 0; k < K; k += 64) { // l.size*l.size*l.c - one filter size [27 - 9216] + uint64_t a_bit64 = *((uint64_t *)(A + (i*lda + k) / 8)); + uint64_t b_bit64 = *((uint64_t *)(B + (j*ldb + k) / 8)); + uint64_t c_bit64 = xnor_int64(a_bit64, b_bit64); + +#ifdef WIN32 + int tmp_count = __popcnt64(c_bit64); +#else + int tmp_count = __builtin_popcountll(c_bit64); +#endif + + if (K - k < 64) tmp_count = tmp_count - (64 - (K - k)); // remove extra bits + count += tmp_count; + //binary_int64_printf(c_bit64); + //printf(", count = %d \n\n", tmp_count); + } + + C[i*ldc + j] = (2 * count - K) * mean_val; + } + } +} + +//From Berkeley Vision's Caffe! +//https://github.com/BVLC/caffe/blob/master/LICENSE +void im2col_cpu_custom(float* data_im, + int channels, int height, int width, + int ksize, int stride, int pad, float* data_col) +{ + + int c, h, w; + int height_col = (height + 2 * pad - ksize) / stride + 1; + int width_col = (width + 2 * pad - ksize) / stride + 1; + int channels_col = channels * ksize * ksize; + + // optimized version + if (height_col == height && width_col == width && stride == 1 && pad == 1) + { + #pragma omp parallel for + 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 = pad; h < height_col - pad; ++h) { + for (w = pad; w < width_col - pad; ++w) { + int im_row = h_offset + h - pad; + int im_col = w_offset + w - pad; + int col_index = (c * height_col + h) * width_col + w; + + data_col[col_index] = data_im[im_col + width*(im_row + height*c_im)]; + } + + for (; w < width_col - pad; ++w) { + int im_row = h_offset + h - pad; + int im_col = w_offset + w - pad; + int col_index = (c * height_col + h) * width_col + w; + + data_col[col_index] = data_im[im_col + width*(im_row + height*c_im)]; + } +} + + { + w = 0; + for (h = 0; h < height_col; ++h) { + int im_row = h_offset + h; + int im_col = w_offset + w; + int col_index = (c * height_col + h) * width_col + w; + data_col[col_index] = im2col_get_pixel(data_im, height, width, channels, + im_row, im_col, c_im, pad); + } + } + + { + w = width_col - 1; + for (h = 0; h < height_col; ++h) { + int im_row = h_offset + h; + int im_col = w_offset + w; + int col_index = (c * height_col + h) * width_col + w; + data_col[col_index] = im2col_get_pixel(data_im, height, width, channels, + im_row, im_col, c_im, pad); + } + } + + { + h = 0; + for (w = 0; w < width_col; ++w) { + int im_row = h_offset + h; + int im_col = w_offset + w; + int col_index = (c * height_col + h) * width_col + w; + data_col[col_index] = im2col_get_pixel(data_im, height, width, channels, + im_row, im_col, c_im, pad); + } + } + + { + h = height_col - 1; + for (w = 0; w < width_col; ++w) { + int im_row = h_offset + h; + int im_col = w_offset + w; + int col_index = (c * height_col + h) * width_col + w; + data_col[col_index] = im2col_get_pixel(data_im, height, width, channels, + im_row, im_col, c_im, pad); + } + } + } + + } + else { + //printf("\n Error: is no non-optimized version \n"); + im2col_cpu(data_im, channels, height, width, ksize, stride, pad, data_col); + } +} + +void activate_array_cpu_custom(float *x, const int n, const ACTIVATION a) +{ + int i; + if (a == LINEAR) + { + } + else if (a == LEAKY) + { + for (i = 0; i < n; ++i) { + x[i] = (x[i]>0) ? x[i] : .1*x[i]; + } + } + else { + for (i = 0; i < n; ++i) { + x[i] = activate(x[i], a); + } + } +} + +void float_to_bit(float *src, unsigned char *dst, size_t size) +{ + size_t dst_size = size / 8 + 1; + memset(dst, 0, dst_size); + + size_t i; + char *byte_arr = calloc(size, sizeof(char)); + for (i = 0; i < size; ++i) { + if (src[i] > 0) byte_arr[i] = 1; + } + + //for (i = 0; i < size; ++i) { + // dst[i / 8] |= byte_arr[i] << (i % 8); + //} + + for (i = 0; i < size; i += 8) { + char dst_tmp = 0; + dst_tmp |= byte_arr[i + 0] << 0; + dst_tmp |= byte_arr[i + 1] << 1; + dst_tmp |= byte_arr[i + 2] << 2; + dst_tmp |= byte_arr[i + 3] << 3; + dst_tmp |= byte_arr[i + 4] << 4; + dst_tmp |= byte_arr[i + 5] << 5; + dst_tmp |= byte_arr[i + 6] << 6; + dst_tmp |= byte_arr[i + 7] << 7; + dst[i / 8] = dst_tmp; + } + free(byte_arr); +} + +static inline void transpose_scalar_block(float *A, float *B, const int lda, const int ldb, const int block_size) +{ + int i, j; + //#pragma omp parallel for + for (i = 0; i + +void gemm_ongpu(int TA, int TB, int M, int N, int K, float ALPHA, + float *A_gpu, int lda, + float *B_gpu, int ldb, + float BETA, + float *C_gpu, int 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_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) +{ + 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); + + cuda_pull_array(C_gpu, C, ldc*M); + cuda_free(A_gpu); + cuda_free(B_gpu); + cuda_free(C_gpu); +} + +#include +#include +#include +#include + +void time_gpu_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<32; ++i){ + gemm_gpu(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 s\n",m,k,k,n, TA, TB, (float)(end-start)/CLOCKS_PER_SEC); + free(a); + free(b); + free(c); +} + +void time_ongpu(int TA, int TB, int m, int k, int n) +{ + int iter = 10; + float *a = random_matrix(m,k); + float *b = random_matrix(k,n); + + int lda = (!TA)?k:m; + int ldb = (!TB)?n:k; + + float *c = random_matrix(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 static inline void set_bit(unsigned char *const dst, size_t index) { size_t dst_i = index / 8;