From dbdd31ee211fe8b1ac7e93ceadf7b34b8d304f34 Mon Sep 17 00:00:00 2001
From: Roland Singer <roland.singer@desertbit.com>
Date: Wed, 22 Aug 2018 11:56:41 +0000
Subject: [PATCH] updated README to include information about learning rate adjustment for multiple GPUs
---
src/gemm.c | 509 ++++++++++++++++++++++++++++++++++++++++++++++++++------
1 files changed, 454 insertions(+), 55 deletions(-)
diff --git a/src/gemm.c b/src/gemm.c
index 75ce59c..7abfe25 100644
--- a/src/gemm.c
+++ b/src/gemm.c
@@ -5,6 +5,7 @@
#include <stdlib.h>
#include <stdio.h>
#include <math.h>
+#include <float.h>
#if defined(_OPENMP)
#include <omp.h>
@@ -306,18 +307,30 @@
#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>
+#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>
@@ -325,6 +338,14 @@
#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;
@@ -341,35 +362,121 @@
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);
+// Windows
+#define cpuid(info, x) __cpuidex(info, x, 0)
#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]);
+// GCC Intrinsics
+void cpuid(int info[4], int InfoType) {
+ __cpuid_count(InfoType, 0, info[0], info[1], info[2], info[3]);
+}
#endif
- if ((regs[2] & idFeature) != idFeature)
- return 0;
- return 1;
+
+// Misc.
+static int HW_MMX, HW_x64, HW_RDRAND, HW_BMI1, HW_BMI2, HW_ADX, HW_PREFETCHWT1;
+static int HW_ABM; // Advanced Bit Manipulation
+
+// SIMD: 128-bit
+static int HW_SSE, HW_SSE2, HW_SSE3, HW_SSSE3, HW_SSE41, HW_SSE42, HW_SSE4a, HW_AES, HW_SHA;
+
+// SIMD: 256-bit
+static int HW_AVX, HW_XOP, HW_FMA3, HW_FMA4, HW_AVX2;
+
+// SIMD: 512-bit
+static int HW_AVX512F; // AVX512 Foundation
+static int HW_AVX512CD; // AVX512 Conflict Detection
+static int HW_AVX512PF; // AVX512 Prefetch
+static int HW_AVX512ER; // AVX512 Exponential + Reciprocal
+static int HW_AVX512VL; // AVX512 Vector Length Extensions
+static int HW_AVX512BW; // AVX512 Byte + Word
+static int HW_AVX512DQ; // AVX512 Doubleword + Quadword
+static int HW_AVX512IFMA; // AVX512 Integer 52-bit Fused Multiply-Add
+static int HW_AVX512VBMI; // AVX512 Vector Byte Manipulation Instructions
+
+// https://stackoverflow.com/questions/6121792/how-to-check-if-a-cpu-supports-the-sse3-instruction-set
+void check_cpu_features(void) {
+ int info[4];
+ cpuid(info, 0);
+ int nIds = info[0];
+
+ cpuid(info, 0x80000000);
+ unsigned nExIds = info[0];
+
+ // Detect Features
+ if (nIds >= 0x00000001) {
+ cpuid(info, 0x00000001);
+ HW_MMX = (info[3] & ((int)1 << 23)) != 0;
+ HW_SSE = (info[3] & ((int)1 << 25)) != 0;
+ HW_SSE2 = (info[3] & ((int)1 << 26)) != 0;
+ HW_SSE3 = (info[2] & ((int)1 << 0)) != 0;
+
+ HW_SSSE3 = (info[2] & ((int)1 << 9)) != 0;
+ HW_SSE41 = (info[2] & ((int)1 << 19)) != 0;
+ HW_SSE42 = (info[2] & ((int)1 << 20)) != 0;
+ HW_AES = (info[2] & ((int)1 << 25)) != 0;
+
+ HW_AVX = (info[2] & ((int)1 << 28)) != 0;
+ HW_FMA3 = (info[2] & ((int)1 << 12)) != 0;
+
+ HW_RDRAND = (info[2] & ((int)1 << 30)) != 0;
+ }
+ if (nIds >= 0x00000007) {
+ cpuid(info, 0x00000007);
+ HW_AVX2 = (info[1] & ((int)1 << 5)) != 0;
+
+ HW_BMI1 = (info[1] & ((int)1 << 3)) != 0;
+ HW_BMI2 = (info[1] & ((int)1 << 8)) != 0;
+ HW_ADX = (info[1] & ((int)1 << 19)) != 0;
+ HW_SHA = (info[1] & ((int)1 << 29)) != 0;
+ HW_PREFETCHWT1 = (info[2] & ((int)1 << 0)) != 0;
+
+ HW_AVX512F = (info[1] & ((int)1 << 16)) != 0;
+ HW_AVX512CD = (info[1] & ((int)1 << 28)) != 0;
+ HW_AVX512PF = (info[1] & ((int)1 << 26)) != 0;
+ HW_AVX512ER = (info[1] & ((int)1 << 27)) != 0;
+ HW_AVX512VL = (info[1] & ((int)1 << 31)) != 0;
+ HW_AVX512BW = (info[1] & ((int)1 << 30)) != 0;
+ HW_AVX512DQ = (info[1] & ((int)1 << 17)) != 0;
+ HW_AVX512IFMA = (info[1] & ((int)1 << 21)) != 0;
+ HW_AVX512VBMI = (info[2] & ((int)1 << 1)) != 0;
+ }
+ if (nExIds >= 0x80000001) {
+ cpuid(info, 0x80000001);
+ HW_x64 = (info[3] & ((int)1 << 29)) != 0;
+ HW_ABM = (info[2] & ((int)1 << 5)) != 0;
+ HW_SSE4a = (info[2] & ((int)1 << 6)) != 0;
+ HW_FMA4 = (info[2] & ((int)1 << 16)) != 0;
+ HW_XOP = (info[2] & ((int)1 << 11)) != 0;
+ }
}
-int is_fma_avx() {
+int is_avx() {
static int result = -1;
if (result == -1) {
- result = simd_detect_x86(AVXFlag);
+ check_cpu_features();
+ result = HW_AVX;
if (result == 1) printf(" Used AVX \n");
else printf(" Not used AVX \n");
}
return result;
}
+int is_fma_avx2() {
+ static int result = -1;
+ if (result == -1) {
+ check_cpu_features();
+ result = HW_FMA3 && HW_AVX2;
+ if (result == 1) printf(" Used FMA & AVX2 \n");
+ else printf(" Not used FMA & AVX2 \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,
@@ -377,7 +484,7 @@
float *C, int ldc)
{
int i, j, k;
- if (is_fma_avx() == 1) { // AVX
+ if (is_avx() == 1) { // AVX
for (i = 0; i < M; ++i) {
for (k = 0; k < K; ++k) {
float A_PART = ALPHA*A[i*lda + k];
@@ -429,7 +536,7 @@
}
-void convolution_2d(int w, int h, int ksize, int n, int c, int pad, int stride,
+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
@@ -477,6 +584,130 @@
}
}
+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( 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
@@ -516,12 +747,18 @@
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 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,
@@ -533,7 +770,7 @@
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);
+ //omp_set_num_threads(max_num_threads / 2);
}
#endif
@@ -564,10 +801,14 @@
}
// 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 = 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)
@@ -616,15 +857,15 @@
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((__m256i *)(&data_im[im_col + width*(im_row + height*c_im)]));
- data_col[col_index + ldb_align * 0] = src256.m256_f32[0];
- data_col[col_index + ldb_align * 1] = src256.m256_f32[1];
- data_col[col_index + ldb_align * 2] = src256.m256_f32[2];
- data_col[col_index + ldb_align * 3] = src256.m256_f32[3];
- data_col[col_index + ldb_align * 4] = src256.m256_f32[4];
- data_col[col_index + ldb_align * 5] = src256.m256_f32[5];
- data_col[col_index + ldb_align * 6] = src256.m256_f32[6];
- data_col[col_index + ldb_align * 7] = src256.m256_f32[7];
+ __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);
}
@@ -717,7 +958,7 @@
int channels_col = channels * ksize * ksize;
// optimized version
- if (height_col == height && width_col == width && stride == 1 && pad == 1)
+ if (height_col == height && width_col == width && stride == 1 && pad == 1 && is_fma_avx2())
{
#pragma omp parallel for
for (c = 0; c < channels_col; ++c) {
@@ -731,7 +972,7 @@
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)]));
+ __m256 src256 = _mm256_loadu_ps((float *)(&data_im[im_col + width*(im_row + height*c_im)]));
_mm256_storeu_ps(&data_col[col_index], src256);
}
@@ -796,26 +1037,51 @@
}
}
+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;
+ int i = 0;
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);
+ if (is_fma_avx2()) {
+ __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];
+ for (i = 0; i < n - 8; 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
+ __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
+ __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);
+ __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) {
@@ -902,6 +1168,100 @@
}
+void forward_maxpool_layer_avx(float *src, float *dst, int *indexes, int size, int w, int h, int out_w, int out_h, int c,
+ int pad, int stride, int batch)
+{
+
+ int w_offset = -pad / 2;
+ int h_offset = -pad / 2;
+ int b, k;
+
+ for (b = 0; b < batch; ++b) {
+ #pragma omp parallel for
+ for (k = 0; k < c; ++k) {
+ int i, j, m, n;
+ for (i = 0; i < out_h; ++i) {
+ //for (j = 0; j < out_w; ++j) {
+ j = 0;
+
+ if(stride == 1 && is_avx() == 1) {
+ for (j = 0; j < out_w - 8 - (size - 1); j += 8) {
+ int out_index = j + out_w*(i + out_h*(k + c*b));
+ __m256 max256 = _mm256_set1_ps(-FLT_MAX);
+ for (n = 0; n < size; ++n) {
+ for (m = 0; m < size; ++m) {
+ int cur_h = h_offset + i*stride + n;
+ int cur_w = w_offset + j*stride + m;
+ int index = cur_w + w*(cur_h + h*(k + b*c));
+ int valid = (cur_h >= 0 && cur_h < h &&
+ cur_w >= 0 && cur_w < w);
+ if (!valid) continue;
+
+ __m256 src256 = _mm256_loadu_ps(&src[index]);
+ max256 = _mm256_max_ps(src256, max256);
+ }
+ }
+ _mm256_storeu_ps(&dst[out_index], max256);
+
+ }
+ }
+ else if (size == 2 && stride == 2 && is_avx() == 1) {
+ for (j = 0; j < out_w - 4; j += 4) {
+ int out_index = j + out_w*(i + out_h*(k + c*b));
+ float max = -FLT_MAX;
+ int max_i = -1;
+ __m128 max128 = _mm_set1_ps(-FLT_MAX);
+
+ for (n = 0; n < size; ++n) {
+ //for (m = 0; m < size; ++m)
+ m = 0;
+ {
+ int cur_h = h_offset + i*stride + n;
+ int cur_w = w_offset + j*stride + m;
+ int index = cur_w + w*(cur_h + h*(k + b*c));
+ int valid = (cur_h >= 0 && cur_h < h &&
+ cur_w >= 0 && cur_w < w);
+ if (!valid) continue;
+
+ __m256 src256 = _mm256_loadu_ps(&src[index]);
+ __m256 src256_2 = _mm256_permute_ps(src256, (1 << 0) | (3 << 4));
+ __m256 max256 = _mm256_max_ps(src256, src256_2);
+
+ __m128 src128_0 = _mm256_extractf128_ps(max256, 0);
+ __m128 src128_1 = _mm256_extractf128_ps(max256, 1);
+ __m128 src128 = _mm_shuffle_ps(src128_0, src128_1, (2 << 2) | (2 << 6));
+
+ max128 = _mm_max_ps(src128, max128);
+ }
+ }
+ _mm_storeu_ps(&dst[out_index], max128);
+ }
+ }
+
+ for (; j < out_w; ++j) {
+ int out_index = j + out_w*(i + out_h*(k + c*b));
+ float max = -FLT_MAX;
+ int max_i = -1;
+ for (n = 0; n < size; ++n) {
+ for (m = 0; m < size; ++m) {
+ int cur_h = h_offset + i*stride + n;
+ int cur_w = w_offset + j*stride + m;
+ int index = cur_w + w*(cur_h + h*(k + b*c));
+ int valid = (cur_h >= 0 && cur_h < h &&
+ cur_w >= 0 && cur_w < w);
+ float val = (valid != 0) ? src[index] : -FLT_MAX;
+ max_i = (val > max) ? index : max_i;
+ max = (val > max) ? val : max;
+ }
+ }
+ dst[out_index] = max;
+ indexes[out_index] = max_i;
+ }
+ }
+ }
+ }
+}
+
#else
void gemm_nn(int M, int N, int K, float ALPHA,
@@ -922,7 +1282,7 @@
void convolution_2d(int w, int h, int ksize, int n, int c, int pad, int stride,
- float *weights, float *input, float *output)
+ 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
@@ -1018,6 +1378,8 @@
int channels, int height, int width,
int ksize, int stride, int pad, float* data_col)
{
+ im2col_cpu(data_im, channels, height, width, ksize, stride, pad, data_col);
+ return;
int c, h, w;
int height_col = (height + 2 * pad - ksize) / stride + 1;
@@ -1039,7 +1401,7 @@
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;
@@ -1048,7 +1410,7 @@
data_col[col_index] = data_im[im_col + width*(im_row + height*c_im)];
}
-}
+ }
{
w = 0;
@@ -1180,7 +1542,44 @@
}
}
}
-#endif // __x86_64
+
+void forward_maxpool_layer_avx(float *src, float *dst, int *indexes, int size, int w, int h, int out_w, int out_h, int c,
+ int pad, int stride, int batch)
+{
+ int b, k;
+ int w_offset = -pad / 2;
+ int h_offset = -pad / 2;
+
+ for (b = 0; b < batch; ++b) {
+ #pragma omp parallel for
+ for (k = 0; k < c; ++k) {
+ int i, j, m, n;
+ for (i = 0; i < out_h; ++i) {
+ for (j = 0; j < out_w; ++j) {
+ int out_index = j + out_w*(i + out_h*(k + c*b));
+ float max = -FLT_MAX;
+ int max_i = -1;
+ for (n = 0; n < size; ++n) {
+ for (m = 0; m < size; ++m) {
+ int cur_h = h_offset + i*stride + n;
+ int cur_w = w_offset + j*stride + m;
+ int index = cur_w + w*(cur_h + h*(k + b*c));
+ int valid = (cur_h >= 0 && cur_h < h &&
+ cur_w >= 0 && cur_w < w);
+ float val = (valid != 0) ? src[index] : -FLT_MAX;
+ max_i = (val > max) ? index : max_i;
+ max = (val > max) ? val : max;
+ }
+ }
+ dst[out_index] = max;
+ indexes[out_index] = max_i;
+ }
+ }
+ }
+ }
+}
+
+#endif // AVX
void gemm_nt(int M, int N, int K, float ALPHA,
float *A, int lda,
--
Gitblit v1.10.0