From 3baf534a2d603f6b20a06ca45c29350e52a859fb Mon Sep 17 00:00:00 2001
From: AlexeyAB <alexeyab84@gmail.com>
Date: Thu, 09 Aug 2018 00:07:06 +0000
Subject: [PATCH] Compile error fix
---
src/gemm.h | 1
src/gemm.c | 2427 +++++++++++++++++++++++++++++-----------------------------
2 files changed, 1,218 insertions(+), 1,210 deletions(-)
diff --git a/src/gemm.c b/src/gemm.c
index 478e966..ff5edfa 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 <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,
- 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 <stdint.h>
-
-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 <intrin.h>
-#include <ammintrin.h>
-#include <immintrin.h>
-#include <smmintrin.h>
-
-#else // Linux GCC/Clang
-#include <x86intrin.h>
-#include <ammintrin.h>
-#include <immintrin.h>
-#include <smmintrin.h>
-#include <cpuid.h>
-
-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<block_size; i++) {
- for (j = 0; j<block_size; j++) {
- B[j*ldb + i] = A[i*lda + j];
- }
- }
-}
-
-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;
- #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];
- }
- }
- }
- }
-}
-#endif // __x86_64
-
-void gemm_nt(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(j = 0; j < N; ++j){
- register float sum = 0;
- for(k = 0; k < K; ++k){
- sum += ALPHA*A[i*lda+k]*B[j*ldb + k];
- }
- C[i*ldc+j] += sum;
- }
- }
-}
-
-void gemm_tn(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[k*lda+i];
- for(j = 0; j < N; ++j){
- C[i*ldc+j] += A_PART*B[k*ldb+j];
- }
- }
- }
-}
-
-void gemm_tt(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(j = 0; j < N; ++j){
- register float sum = 0;
- for(k = 0; k < K; ++k){
- sum += ALPHA*A[i+k*lda]*B[k+j*ldb];
- }
- C[i*ldc+j] += sum;
- }
- }
-}
-
-
-void gemm_cpu(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)
-{
- //printf("cpu: %d %d %d %d %d %f %d %d %f %d\n",TA, TB, M, N, K, ALPHA, lda, ldb, BETA, ldc);
- if (BETA != 1){
- int i, j;
- for(i = 0; i < M; ++i){
- for(j = 0; j < N; ++j){
- C[i*ldc + j] *= BETA;
- }
- }
- }
-
- 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 <math.h>
-
-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 <stdio.h>
-#include <stdlib.h>
-#include <string.h>
-#include <time.h>
-
-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<iter; ++i){
- gemm_ongpu(TA,TB,m,n,k,1,a_cl,lda,b_cl,ldb,1,c_cl,n);
- cudaThreadSynchronize();
- }
- 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);
- 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);
- 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);
- float *c_gpu = random_matrix(m,n);
- memset(c, 0, m*n*sizeof(float));
- memset(c_gpu, 0, m*n*sizeof(float));
- 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) {
- //printf("%f %f\n", c[i], c_gpu[i]);
- sse += pow(c[i]-c_gpu[i], 2);
- }
- printf("Matrix Multiplication %dx%d * %dx%d, TA=%d, TB=%d: %g SSE\n",m,k,k,n, TA, TB, sse/(m*n));
- free(a);
- free(b);
- free(c);
- free(c_gpu);
-}
-
-int test_gpu_blas()
-{
- /*
- 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(0,0,1000,10,100);
- 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(0,0,10,10,10);
-
- 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
-
+#include "gemm.h"
+#include "utils.h"
+#include "im2col.h"
+#include "cuda.h"
+#include <stdlib.h>
+#include <stdio.h>
+#include <math.h>
+
+#if defined(_OPENMP)
+#include <omp.h>
+#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 <stdint.h>
+
+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 <intrin.h>
+#include <ammintrin.h>
+#include <immintrin.h>
+#include <smmintrin.h>
+
+#else // Linux GCC/Clang
+#include <x86intrin.h>
+#include <ammintrin.h>
+#include <immintrin.h>
+#include <smmintrin.h>
+#include <cpuid.h>
+
+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<block_size; i++) {
+ for (j = 0; j<block_size; j++) {
+ B[j*ldb + i] = A[i*lda + j];
+ }
+ }
+}
+
+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;
+ #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];
+ }
+ }
+ }
+ }
+}
+#endif // __x86_64
+
+void gemm_nt(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(j = 0; j < N; ++j){
+ register float sum = 0;
+ for(k = 0; k < K; ++k){
+ sum += ALPHA*A[i*lda+k]*B[j*ldb + k];
+ }
+ C[i*ldc+j] += sum;
+ }
+ }
+}
+
+void gemm_tn(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[k*lda+i];
+ for(j = 0; j < N; ++j){
+ C[i*ldc+j] += A_PART*B[k*ldb+j];
+ }
+ }
+ }
+}
+
+void gemm_tt(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(j = 0; j < N; ++j){
+ register float sum = 0;
+ for(k = 0; k < K; ++k){
+ sum += ALPHA*A[i+k*lda]*B[k+j*ldb];
+ }
+ C[i*ldc+j] += sum;
+ }
+ }
+}
+
+
+void gemm_cpu(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)
+{
+ //printf("cpu: %d %d %d %d %d %f %d %d %f %d\n",TA, TB, M, N, K, ALPHA, lda, ldb, BETA, ldc);
+ if (BETA != 1){
+ int i, j;
+ for(i = 0; i < M; ++i){
+ for(j = 0; j < N; ++j){
+ C[i*ldc + j] *= BETA;
+ }
+ }
+ }
+
+ 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 <math.h>
+
+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 <stdio.h>
+#include <stdlib.h>
+#include <string.h>
+#include <time.h>
+
+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<iter; ++i){
+ gemm_ongpu(TA,TB,m,n,k,1,a_cl,lda,b_cl,ldb,1,c_cl,n);
+ cudaThreadSynchronize();
+ }
+ 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);
+ 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);
+ 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);
+ float *c_gpu = random_matrix(m,n);
+ memset(c, 0, m*n*sizeof(float));
+ memset(c_gpu, 0, m*n*sizeof(float));
+ 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) {
+ //printf("%f %f\n", c[i], c_gpu[i]);
+ sse += pow(c[i]-c_gpu[i], 2);
+ }
+ printf("Matrix Multiplication %dx%d * %dx%d, TA=%d, TB=%d: %g SSE\n",m,k,k,n, TA, TB, sse/(m*n));
+ free(a);
+ free(b);
+ free(c);
+ free(c_gpu);
+}
+
+int test_gpu_blas()
+{
+ /*
+ 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(0,0,1000,10,100);
+ 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(0,0,10,10,10);
+
+ 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
+
diff --git a/src/gemm.h b/src/gemm.h
index 97fa09c..4514f57 100644
--- a/src/gemm.h
+++ b/src/gemm.h
@@ -1,6 +1,7 @@
#ifndef GEMM_H
#define GEMM_H
#include "activations.h"
+#include <stdint.h>
static inline void set_bit(unsigned char *const dst, size_t index) {
size_t dst_i = index / 8;
--
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