From a723e1c62a27aeb39aaf7fcdeb3beb4e89fba32d Mon Sep 17 00:00:00 2001
From: Alexey <AlexeyAB@users.noreply.github.com>
Date: Wed, 15 Aug 2018 20:52:09 +0000
Subject: [PATCH] Merge pull request #766 from HotChick91/AlexeyAB-mask
---
src/gemm.c | 1465 ++++++++++++++++++++++++++++++++++++++++++++++++++++------
1 files changed, 1,311 insertions(+), 154 deletions(-)
diff --git a/src/gemm.c b/src/gemm.c
index 0efefd0..2fd7f50 100644
--- a/src/gemm.c
+++ b/src/gemm.c
@@ -1,12 +1,17 @@
#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,
+#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)
{
@@ -62,8 +67,8 @@
}
-void gemm(int TA, int TB, int M, int N, int K, float ALPHA,
- float *A, int lda,
+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)
@@ -71,6 +76,234 @@
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)
@@ -79,142 +312,1064 @@
#define CLMULFlag ((1UL<< 1)|AVXFlag|OSXSAVEFlag)
#define VAESFlag ((1UL<<25)|AVXFlag|OSXSAVEFlag)
-#include <stdint.h>
-
#ifdef _WIN64
#include <intrin.h>
#include <ammintrin.h>
#include <immintrin.h>
#include <smmintrin.h>
-#else // Linux GCC/Clang
+#if defined(_MSC_VER) && _MSC_VER <= 1900
+static inline __int32 _mm256_extract_epi64(__m256i a, const int index) {
+ return a.m256i_i64[index];
+}
+
+static inline __int32 _mm256_extract_epi32(__m256i a, const int index) {
+ return a.m256i_i32[index];
+}
+
+#endif
+
+static inline float _castu32_f32(uint32_t a) {
+ return *((float *)&a);
+}
+
+static inline float _mm256_extract_float32(__m256 a, const int index) {
+ return a.m256_f32[index];
+}
+
+#else // Linux GCC/Clang
#include <x86intrin.h>
#include <ammintrin.h>
#include <immintrin.h>
#include <smmintrin.h>
+#include <cpuid.h>
+
+static inline float _castu32_f32(uint32_t a) {
+ return *((float *)&a);
+}
+
+static inline float _mm256_extract_float32(__m256 a, const int index) {
+ return _castu32_f32(_mm256_extract_epi32(_mm256_castps_si256(a), index));
+}
void asm_cpuid(uint32_t* abcd, uint32_t eax)
{
- uint32_t ebx = 0, edx = 0, ecx = 0;
+ 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));
+ // 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;
+ 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;
+ uint32_t regs[4]; // EAX, EBX, ECX, EDX;
#ifdef _WIN32
- __cpuid(regs, 0);
- if (regs[0] > 1U) __cpuid(regs, 1);
+ __cpuid(regs, 0);
+ if (regs[0] > 1U) __cpuid(regs, 1);
#else
- asm_cpuid(regs, 0);
- if (regs[0] > 1U) asm_cpuid(regs, 0);
+ __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;
+ 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;
+ 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)
+ 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 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 % 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];
- }
- */
- }
- }
- }
+ 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];
+ }
+ */
+ }
+ }
+ }
}
+
+
+void convolution_2d_old(int w, int h, int ksize, int n, int c, int pad, int stride,
+ float *weights, float *input, float *output)
+{
+ int out_h = (h + 2 * pad - ksize) / stride + 1; // output_height=input_height for stride=1 and pad=1
+ int out_w = (w + 2 * pad - ksize) / stride + 1; // output_width=input_width for stride=1 and pad=1
+ int i, f, j;
+
+ int fil;
+ // filter index
+#pragma omp parallel for // "omp parallel for" - automatic parallelization of loop by using OpenMP
+ for (fil = 0; fil < n; ++fil) {
+ int chan, y, x, f_y, f_x;
+ // channel index
+ for (chan = 0; chan < c; ++chan)
+ // input - y
+ for (y = 0; y < h; ++y)
+ // input - x
+ for (x = 0; x < w; ++x)
+ {
+ int const output_index = fil*w*h + y*w + x;
+ int const weights_pre_index = fil*c*ksize*ksize + chan*ksize*ksize;
+ int const input_pre_index = chan*w*h;
+ float sum = 0;
+
+ // filter - y
+ for (f_y = 0; f_y < ksize; ++f_y)
+ {
+ int input_y = y + f_y - pad;
+ // filter - x
+ for (f_x = 0; f_x < ksize; ++f_x)
+ {
+ int input_x = x + f_x - pad;
+ if (input_y < 0 || input_x < 0 || input_y >= h || input_x >= w) continue;
+
+ int input_index = input_pre_index + input_y*w + input_x;
+ int weights_index = weights_pre_index + f_y*ksize + f_x;
+
+ sum += input[input_index] * weights[weights_index];
+ }
+ }
+ // l.output[filters][width][height] +=
+ // state.input[channels][width][height] *
+ // l.weights[filters][channels][filter_width][filter_height];
+ output[output_index] += sum;
+ }
+ }
+}
+
+void convolution_2d(int w, int h, int ksize, int n, int c, int pad, int stride,
+ float *weights, float *input, float *output, float *mean)
+{
+ int out_h = (h + 2 * pad - ksize) / stride + 1; // output_height=input_height for stride=1 and pad=1
+ int out_w = (w + 2 * pad - ksize) / stride + 1; // output_width=input_width for stride=1 and pad=1
+ int i, f, j;
+
+#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(4);// max_num_threads / 2);
+ }
+#endif
+
+ //convolution_2d_old(w, h, ksize, n, c, pad, stride, weights, input, output);
+
+ __m256i all256_sing1 = _mm256_set_epi32(0x80000000, 0x80000000, 0x80000000, 0x80000000, 0x80000000, 0x80000000, 0x80000000, 0x80000000);
+ for (i = 0; i < ksize*ksize*n*c; i+=8) {
+ *((__m256*)&weights[i]) = _mm256_and_ps(*((__m256*)&weights[i]), _mm256_castsi256_ps(all256_sing1));
+ }
+
+ for (i = 0; i < w*h*c; i += 8) {
+ //*((__m256*)&input[i]) = _mm256_and_ps(*((__m256*)&input[i]), _mm256_castsi256_ps(all256_sing1));
+ }
+
+
+ //__m256i all256_last_zero = _mm256_set1_epi32(0xFFFFFFFF);
+ //all256_last_zero.m256i_i32[7] = 0;
+ __m256i all256_last_zero =
+ _mm256_set_epi32(0xFFFFFFFF, 0xFFFFFFFF, 0xFFFFFFFF, 0xFFFFFFFF, 0xFFFFFFFF, 0xFFFFFFFF, 0xFFFFFFFF, 0x0);
+
+ __m256i idx256 = _mm256_set_epi32(0, 7, 6, 5, 4, 3, 2, 1);
+ //__m256 all256_sing1 = _mm256_set1_ps(0x80000000);
+ __m256 all256_one = _mm256_set1_ps(1);
+ __m256i all256i_one = _mm256_set1_epi32(1);
+
+ ///__m256i src256 = _mm256_loadu_si256((__m256i *)(&src[i]));
+ ///__m256i result256 = _mm256_and_si256(src256, all256_sing1); // check sign in 8 x 32-bit floats
+
+ int fil;
+ // filter index
+#pragma omp parallel for // "omp parallel for" - automatic parallelization of loop by using OpenMP
+ for (fil = 0; fil < n; ++fil) {
+ int chan, y, x, f_y, f_x;
+ float cur_mean = fabs(mean[fil]);
+ __m256 mean256 = _mm256_set1_ps(cur_mean);
+ // channel index
+ //for (chan = 0; chan < c; ++chan)
+ // input - y
+ for (y = 0; y < h; ++y)
+ // input - x
+ for (x = 0; x < w-8; x+=8)
+ {
+ int const output_index = fil*w*h + y*w + x;
+ float sum = 0;
+ __m256 sum256 = _mm256_set1_ps(0);
+
+ for (chan = 0; chan < c; ++chan) {
+ int const weights_pre_index = fil*c*ksize*ksize + chan*ksize*ksize;
+ int const input_pre_index = chan*w*h;
+
+
+ // filter - y
+ for (f_y = 0; f_y < ksize; ++f_y)
+ {
+ int input_y = y + f_y - pad;
+ //__m256 in = *((__m256*)&input[input_pre_index + input_y*w]);
+ if (input_y < 0 || input_y >= h) continue;
+ //__m256 in = _mm256_loadu_ps(&input[input_pre_index + input_y*w + x - pad]);
+
+ // filter - x
+ for (f_x = 0; f_x < ksize; ++f_x)
+ {
+ int input_x = x + f_x - pad;
+ //if (input_y < 0 || input_x < 0 || input_y >= h || input_x >= w) continue;
+
+ int input_index = input_pre_index + input_y*w + input_x;
+ int weights_index = weights_pre_index + f_y*ksize + f_x;
+ //if (input_y < 0 || input_y >= h) continue;
+
+ //sum += input[input_index] * weights[weights_index];
+
+ __m256 in = *((__m256*)&input[input_index]);
+ __m256 w = _mm256_set1_ps(weights[weights_index]);
+ //__m256 w_sign = _mm256_and_ps(w, _mm256_castsi256_ps(all256_sing1)); // check sign in 8 x 32-bit floats
+ __m256 xor256 = _mm256_xor_ps(w, in);
+ //printf("\n xor256_1 = %f, xor256_2 = %f \n", xor256.m256_f32[0], xor256.m256_f32[1]);
+ //printf("\n in = %f, w = %f, xor256 = %f \n", in.m256_f32[0], w_sign.m256_f32[0], xor256.m256_f32[0]);
+
+ //__m256 pn1 = _mm256_and_ps(_mm256_castsi256_ps(all256i_one), xor256);
+
+
+ //sum256 = xor256;
+ sum256 = _mm256_add_ps(xor256, sum256);
+ //printf("\n --- \n");
+ //printf("\n 0 = %f, 1 = %f, 2 = %f, 3 = %f, 4 = %f, 5 = %f, 6 = %f, 7 = %f \n", in.m256_f32[0], in.m256_f32[1], in.m256_f32[2], in.m256_f32[3], in.m256_f32[4], in.m256_f32[5], in.m256_f32[6], in.m256_f32[7]);
+
+ if (f_x < ksize-1) {
+ //in = _mm256_permutevar8x32_ps(in, idx256);
+ //in = _mm256_and_ps(in, _mm256_castsi256_ps(all256_last_zero));
+ }
+ }
+ }
+ }
+ // l.output[filters][width][height] +=
+ // state.input[channels][width][height] *
+ // l.weights[filters][channels][filter_width][filter_height];
+ //output[output_index] += sum;
+
+ sum256 = _mm256_mul_ps(sum256, mean256);
+ //printf("\n cur_mean = %f, sum256 = %f, sum256 = %f, in = %f \n",
+ // cur_mean, sum256.m256_f32[0], sum256.m256_f32[1], input[input_pre_index]);
+
+ //__m256 out = *((__m256*)&output[output_index]);
+ //out = _mm256_add_ps(out, sum256);
+ //*((__m256*)&output[output_index]) = out;
+ *((__m256*)&output[output_index]) = sum256;
+
+ //_mm256_storeu_ps(&C[i*ldc + j], result256);
+ }
+ }
+}
+
+
+
+// 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];
+ return _mm256_extract_epi64(val, 0)
+ + _mm256_extract_epi64(val, 1)
+ + _mm256_extract_epi64(val, 2)
+ + _mm256_extract_epi64(val, 3);
+}
+
+// 5x times faster than gemm()-float32
+// further optimizations: do mean-mult only for the last layer
+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];
+ count = _mm256_extract_epi64(count_sum, 0)
+ + _mm256_extract_epi64(count_sum, 1)
+ + _mm256_extract_epi64(count_sum, 2)
+ + _mm256_extract_epi64(count_sum, 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_transpose(float* data_im,
+ int channels, int height, int width,
+ int ksize, int stride, int pad, float* data_col, int ldb_align)
+{
+ 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 - 4; 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;
+ int col_index = (h * width_col + w)*ldb_align + c; // transposed & aligned
+
+ //data_col[col_index] = data_im[im_col + width*(im_row + height*c_im)];
+ __m256 src256 = _mm256_loadu_ps((float *)(&data_im[im_col + width*(im_row + height*c_im)]));
+ data_col[col_index + ldb_align * 0] = _mm256_extract_float32(src256, 0);// src256.m256_f32[0];
+ data_col[col_index + ldb_align * 1] = _mm256_extract_float32(src256, 1);// src256.m256_f32[1];
+ data_col[col_index + ldb_align * 2] = _mm256_extract_float32(src256, 2);// src256.m256_f32[2];
+ data_col[col_index + ldb_align * 3] = _mm256_extract_float32(src256, 3);// src256.m256_f32[3];
+ data_col[col_index + ldb_align * 4] = _mm256_extract_float32(src256, 4);// src256.m256_f32[4];
+ data_col[col_index + ldb_align * 5] = _mm256_extract_float32(src256, 5);// src256.m256_f32[5];
+ data_col[col_index + ldb_align * 6] = _mm256_extract_float32(src256, 6);// src256.m256_f32[6];
+ data_col[col_index + ldb_align * 7] = _mm256_extract_float32(src256, 7);// src256.m256_f32[7];
+
+ //_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 = (h * width_col + w)*ldb_align + c; // transposed & aligned
+ 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 = (h * width_col + w)*ldb_align + c; // transposed & aligned
+ 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 = (h * width_col + w)*ldb_align + c; // transposed & aligned
+ 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 = (h * width_col + w)*ldb_align + c; // transposed & aligned
+ 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 = (h * width_col + w)*ldb_align + c; // transposed & aligned
+ data_col[col_index] = im2col_get_pixel(data_im, height, width, channels,
+ im_row, im_col, c_im, pad);
+ }
+ }
+ }
+
+ }
+ else {
+ #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 = 0; h < height_col; ++h) {
+ for (w = 0; w < width_col; ++w) {
+ int im_row = h_offset + h * stride;
+ int im_col = w_offset + w * stride;
+
+ int col_index = (h * width_col + w)*ldb_align + c; // transposed & aligned
+ data_col[col_index] = im2col_get_pixel(data_im, height, width, channels,
+ im_row, im_col, c_im, pad);
+ }
+ }
+ }
+ }
+}
+
+
+//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 && is_fma_avx())
+ {
+ #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((float *)(&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 transpose_8x8_bits(unsigned char A[8], unsigned char B[8], int m, int n)
+{
+ unsigned x, y, t;
+
+ // Load the array and pack it into x and y.
+
+ x = (A[0] << 24) | (A[m] << 16) | (A[2 * m] << 8) | A[3 * m];
+ y = (A[4 * m] << 24) | (A[5 * m] << 16) | (A[6 * m] << 8) | A[7 * m];
+
+ t = (x ^ (x >> 7)) & 0x00AA00AA; x = x ^ t ^ (t << 7);
+ t = (y ^ (y >> 7)) & 0x00AA00AA; y = y ^ t ^ (t << 7);
+
+ t = (x ^ (x >> 14)) & 0x0000CCCC; x = x ^ t ^ (t << 14);
+ t = (y ^ (y >> 14)) & 0x0000CCCC; y = y ^ t ^ (t << 14);
+
+ t = (x & 0xF0F0F0F0) | ((y >> 4) & 0x0F0F0F0F);
+ y = ((x << 4) & 0xF0F0F0F0) | (y & 0x0F0F0F0F);
+ x = t;
+
+ B[0] = x >> 24; B[n] = x >> 16; B[2 * n] = x >> 8; B[3 * n] = x;
+ B[4 * n] = y >> 24; B[5 * n] = y >> 16; B[6 * n] = y >> 8; B[7 * n] = y;
+}
+
+void activate_array_cpu_custom(float *x, const int n, const ACTIVATION a)
+{
+ int i = 0;
+ if (a == LINEAR)
+ {}
+ else if (a == LEAKY)
+ {
+ if (is_fma_avx()) {
+ __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 - 8; i += 8) {
+ //x[i] = (x[i]>0) ? x[i] : .1*x[i];
+
+ __m256 src256 = _mm256_loadu_ps(&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(&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_loadu_ps(&A[0 * lda]);
+ __m128 row2 = _mm_loadu_ps(&A[1 * lda]);
+ __m128 row3 = _mm_loadu_ps(&A[2 * lda]);
+ __m128 row4 = _mm_loadu_ps(&A[3 * lda]);
+ _MM_TRANSPOSE4_PS(row1, row2, row3, row4);
+ _mm_storeu_ps(&B[0 * ldb], row1);
+ _mm_storeu_ps(&B[1 * ldb], row2);
+ _mm_storeu_ps(&B[2 * ldb], row3);
+ _mm_storeu_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;
+ #pragma omp parallel for
+ for (i = 0; i < n; i += block_size) {
+ int j, i2, j2;
+ //int max_i2 = (i + block_size < n) ? (i + block_size) : n;
+ if (i + block_size < n) {
+ int max_i2 = i + block_size;
+ for (j = 0; j < m; j += block_size) {
+ //int max_j2 = (j + block_size < m) ? (j + block_size) : m;
+ if (j + block_size < m) {
+ int max_j2 = j + block_size;
+ 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 {
+ for (i2 = i; i2 < max_i2; ++i2) {
+ for (j2 = j; j2 < m; ++j2) {
+ B[j2*ldb + i2] = A[i2*lda + j2];
+ }
+ }
+ }
+ }
+ }
+ else {
+ for (i2 = i; i2 < n; ++i2) {
+ for (j2 = 0; j2 < m; ++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)
+ 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];
- }
- }
- }
+ 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];
+ }
+ }
+ }
}
-#endif // __x86_64
-void gemm_nt(int M, int N, int K, float ALPHA,
- float *A, int lda,
+
+void convolution_2d(int w, int h, int ksize, int n, int c, int pad, int stride,
+ float *weights, float *input, float *output, float *mean)
+{
+ int out_h = (h + 2 * pad - ksize) / stride + 1; // output_height=input_height for stride=1 and pad=1
+ int out_w = (w + 2 * pad - ksize) / stride + 1; // output_width=input_width for stride=1 and pad=1
+ int i, f, j;
+
+ int fil;
+ // filter index
+#pragma omp parallel for // "omp parallel for" - automatic parallelization of loop by using OpenMP
+ for (fil = 0; fil < n; ++fil) {
+ int chan, y, x, f_y, f_x;
+ // channel index
+ for (chan = 0; chan < c; ++chan)
+ // input - y
+ for (y = 0; y < h; ++y)
+ // input - x
+ for (x = 0; x < w; ++x)
+ {
+ int const output_index = fil*w*h + y*w + x;
+ int const weights_pre_index = fil*c*ksize*ksize + chan*ksize*ksize;
+ int const input_pre_index = chan*w*h;
+ float sum = 0;
+
+ // filter - y
+ for (f_y = 0; f_y < ksize; ++f_y)
+ {
+ int input_y = y + f_y - pad;
+ // filter - x
+ for (f_x = 0; f_x < ksize; ++f_x)
+ {
+ int input_x = x + f_x - pad;
+ if (input_y < 0 || input_x < 0 || input_y >= h || input_x >= w) continue;
+
+ int input_index = input_pre_index + input_y*w + input_x;
+ int weights_index = weights_pre_index + f_y*ksize + f_x;
+
+ sum += input[input_index] * weights[weights_index];
+ }
+ }
+ // l.output[filters][width][height] +=
+ // state.input[channels][width][height] *
+ // l.weights[filters][channels][filter_width][filter_height];
+ output[output_index] += sum;
+ }
+ }
+}
+
+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;
+ }
+ }
+}
+
+void im2col_cpu_custom_transpose(float* data_im,
+ int channels, int height, int width,
+ int ksize, int stride, int pad, float* data_col, int ldb_align)
+{
+ printf("\n im2col_cpu_custom_transpose() isn't implemented without AVX \n");
+}
+
+//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)
{
@@ -230,8 +1385,8 @@
}
}
-void gemm_tn(int M, int N, int K, float ALPHA,
- float *A, int lda,
+void gemm_tn(int M, int N, int K, float ALPHA,
+ float *A, int lda,
float *B, int ldb,
float *C, int ldc)
{
@@ -246,8 +1401,8 @@
}
}
-void gemm_tt(int M, int N, int K, float ALPHA,
- float *A, int lda,
+void gemm_tt(int M, int N, int K, float ALPHA,
+ float *A, int lda,
float *B, int ldb,
float *C, int ldc)
{
@@ -264,53 +1419,55 @@
}
-void gemm_cpu(int TA, int TB, int M, int N, int K, float ALPHA,
- float *A, int lda,
+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);
- int i, j;
- for(i = 0; i < M; ++i){
- for(j = 0; j < N; ++j){
- C[i*ldc + j] *= BETA;
+ 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);
- }
+ 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,
+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),
+ 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,
+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)
@@ -431,38 +1588,38 @@
int test_gpu_blas()
{
/*
- test_gpu_accuracy(0,0,10,576,75);
+ test_gpu_accuracy(0,0,10,576,75);
- test_gpu_accuracy(0,0,17,10,10);
- test_gpu_accuracy(1,0,17,10,10);
- test_gpu_accuracy(0,1,17,10,10);
- test_gpu_accuracy(1,1,17,10,10);
+ test_gpu_accuracy(0,0,17,10,10);
+ test_gpu_accuracy(1,0,17,10,10);
+ test_gpu_accuracy(0,1,17,10,10);
+ test_gpu_accuracy(1,1,17,10,10);
- test_gpu_accuracy(0,0,1000,10,100);
- test_gpu_accuracy(1,0,1000,10,100);
- test_gpu_accuracy(0,1,1000,10,100);
- test_gpu_accuracy(1,1,1000,10,100);
+ test_gpu_accuracy(0,0,1000,10,100);
+ 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);
+ 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(0,0,64,2916,363);
+ 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);
+ 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;
}
--
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