mirror of
https://github.com/tesseract-ocr/tesseract.git
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b54894a088
Signed-off-by: Stefan Weil <sw@weilnetz.de>
105 lines
3.8 KiB
C++
105 lines
3.8 KiB
C++
///////////////////////////////////////////////////////////////////////
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// File: dotproductavx.cpp
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// Description: Architecture-specific dot-product function.
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// Author: Ray Smith
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// Created: Wed Jul 22 10:48:05 PDT 2015
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//
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// (C) Copyright 2015, Google Inc.
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// Licensed under the Apache License, Version 2.0 (the "License");
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// you may not use this file except in compliance with the License.
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// You may obtain a copy of the License at
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// http://www.apache.org/licenses/LICENSE-2.0
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// Unless required by applicable law or agreed to in writing, software
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// distributed under the License is distributed on an "AS IS" BASIS,
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// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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// See the License for the specific language governing permissions and
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// limitations under the License.
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///////////////////////////////////////////////////////////////////////
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#if !defined(__AVX__) || defined(__i386__)
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// Implementation for non-avx archs.
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// Also used for 32 bit AVX archs because of missing _mm256_extract_epi64.
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#include "dotproductavx.h"
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#include <stdio.h>
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#include <stdlib.h>
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namespace tesseract {
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double DotProductAVX(const double* u, const double* v, int n) {
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fprintf(stderr, "DotProductAVX can't be used on Android\n");
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abort();
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}
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} // namespace tesseract
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#else // !defined(__AVX__)
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// Implementation for avx capable archs.
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#include <immintrin.h>
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#include <stdint.h>
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#include "dotproductavx.h"
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#include "host.h"
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namespace tesseract {
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// Computes and returns the dot product of the n-vectors u and v.
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// Uses Intel AVX intrinsics to access the SIMD instruction set.
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double DotProductAVX(const double* u, const double* v, int n) {
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int max_offset = n - 4;
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int offset = 0;
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// Accumulate a set of 4 sums in sum, by loading pairs of 4 values from u and
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// v, and multiplying them together in parallel.
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__m256d sum = _mm256_setzero_pd();
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if (offset <= max_offset) {
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offset = 4;
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// Aligned load is reputedly faster but requires 32 byte aligned input.
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if ((reinterpret_cast<const uintptr_t>(u) & 31) == 0 &&
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(reinterpret_cast<const uintptr_t>(v) & 31) == 0) {
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// Use aligned load.
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__m256d floats1 = _mm256_load_pd(u);
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__m256d floats2 = _mm256_load_pd(v);
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// Multiply.
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sum = _mm256_mul_pd(floats1, floats2);
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while (offset <= max_offset) {
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floats1 = _mm256_load_pd(u + offset);
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floats2 = _mm256_load_pd(v + offset);
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offset += 4;
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__m256d product = _mm256_mul_pd(floats1, floats2);
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sum = _mm256_add_pd(sum, product);
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}
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} else {
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// Use unaligned load.
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__m256d floats1 = _mm256_loadu_pd(u);
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__m256d floats2 = _mm256_loadu_pd(v);
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// Multiply.
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sum = _mm256_mul_pd(floats1, floats2);
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while (offset <= max_offset) {
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floats1 = _mm256_loadu_pd(u + offset);
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floats2 = _mm256_loadu_pd(v + offset);
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offset += 4;
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__m256d product = _mm256_mul_pd(floats1, floats2);
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sum = _mm256_add_pd(sum, product);
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}
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}
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}
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// Add the 4 product sums together horizontally. Not so easy as with sse, as
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// there is no add across the upper/lower 128 bit boundary, so permute to
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// move the upper 128 bits to lower in another register.
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__m256d sum2 = _mm256_permute2f128_pd(sum, sum, 1);
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sum = _mm256_hadd_pd(sum, sum2);
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sum = _mm256_hadd_pd(sum, sum);
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double result;
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// _mm256_extract_f64 doesn't exist, but resist the temptation to use an sse
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// instruction, as that introduces a 70 cycle delay. All this casting is to
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// fool the instrinsics into thinking we are extracting the bottom int64.
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*(reinterpret_cast<inT64*>(&result)) =
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_mm256_extract_epi64(_mm256_castpd_si256(sum), 0);
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while (offset < n) {
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result += u[offset] * v[offset];
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++offset;
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}
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return result;
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}
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} // namespace tesseract.
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#endif // ANDROID_BUILD
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