tesseract/src/arch/intsimdmatrixsse.cpp
Stefan Weil 61eab60fe3 arch: Reduce number of include files for dot product functions
dotproductavx.h and dotproductsse.h declared only two functions.
Move those declarations to dotproduct.h.

Signed-off-by: Stefan Weil <sw@weilnetz.de>
2019-07-12 23:18:00 +02:00

105 lines
3.7 KiB
C++

///////////////////////////////////////////////////////////////////////
// File: intsindmatrixsse.cpp
// Description: SSE implementation of 8-bit int SIMD matrix multiply.
// Author: Ray Smith
//
// (C) Copyright 2017, Google Inc.
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
// http://www.apache.org/licenses/LICENSE-2.0
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
///////////////////////////////////////////////////////////////////////
#if !defined(__SSE4_1__)
#error Implementation only for SSE 4.1 capable architectures
#endif
#include "intsimdmatrix.h"
#include <cstdint>
#include <emmintrin.h>
#include <smmintrin.h>
namespace tesseract {
// Computes and returns the dot product of the n-vectors u and v.
// Uses Intel SSE intrinsics to access the SIMD instruction set.
static int32_t IntDotProductSSE(const int8_t* u, const int8_t* v, int n) {
int max_offset = n - 8;
int offset = 0;
// Accumulate a set of 4 32-bit sums in sum, by loading 8 pairs of 8-bit
// values, extending to 16 bit, multiplying to make 32 bit results.
int32_t result = 0;
if (offset <= max_offset) {
offset = 8;
__m128i packed1 = _mm_loadl_epi64(reinterpret_cast<const __m128i*>(u));
__m128i packed2 = _mm_loadl_epi64(reinterpret_cast<const __m128i*>(v));
__m128i sum = _mm_cvtepi8_epi16(packed1);
packed2 = _mm_cvtepi8_epi16(packed2);
// The magic _mm_add_epi16 is perfect here. It multiplies 8 pairs of 16 bit
// ints to make 32 bit results, which are then horizontally added in pairs
// to make 4 32 bit results that still fit in a 128 bit register.
sum = _mm_madd_epi16(sum, packed2);
while (offset <= max_offset) {
packed1 = _mm_loadl_epi64(reinterpret_cast<const __m128i*>(u + offset));
packed2 = _mm_loadl_epi64(reinterpret_cast<const __m128i*>(v + offset));
offset += 8;
packed1 = _mm_cvtepi8_epi16(packed1);
packed2 = _mm_cvtepi8_epi16(packed2);
packed1 = _mm_madd_epi16(packed1, packed2);
sum = _mm_add_epi32(sum, packed1);
}
// Sum the 4 packed 32 bit sums and extract the low result.
sum = _mm_hadd_epi32(sum, sum);
sum = _mm_hadd_epi32(sum, sum);
result = _mm_cvtsi128_si32(sum);
}
while (offset < n) {
result += u[offset] * v[offset];
++offset;
}
return result;
}
// Computes part of matrix.vector v = Wu. Computes 1 result.
static void PartialMatrixDotVector1(const int8_t* wi, const double* scales,
const int8_t* u, int num_in,
double* v) {
double total = IntDotProductSSE(u, wi, num_in);
// Add in the bias and correct for integer values.
*v = (total / INT8_MAX + wi[num_in]) * *scales;
}
static void matrixDotVector(int dim1, int dim2, const int8_t* wi,
const double* scales, const int8_t* u, double* v) {
const int num_out = dim1;
const int num_in = dim2 - 1;
int output = 0;
for (; output < num_out; output++) {
PartialMatrixDotVector1(wi, scales, u, num_in, v);
wi += dim2;
scales++;
v++;
}
}
const IntSimdMatrix IntSimdMatrix::intSimdMatrixSSE = {
matrixDotVector,
// Number of 32 bit outputs held in each register.
1,
// Maximum number of registers that we will use to hold outputs.
1,
// Number of 8 bit inputs in the inputs register.
1,
// Number of inputs in each weight group.
1
};
} // namespace tesseract.