dotproductavx.cpp

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// File:        dotproductavx.cpp
// Description: Architecture-specific dot-product function.
// Author:      Ray Smith
// Created:     Wed Jul 22 10:48:05 PDT 2015
//
// (C) Copyright 2015, 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(__AVX__)
// Implementation for non-avx archs.

#include "dotproductavx.h"
#include <stdio.h>
#include <stdlib.h>

namespace tesseract {
double DotProductAVX(const double* u, const double* v, int n) {
  fprintf(stderr, "DotProductAVX can't be used on Android\n");
  abort();
}
}  // namespace tesseract

#else  // !defined(__AVX__)
// Implementation for avx capable archs.
#include <immintrin.h>
#include <stdint.h>
#include "dotproductavx.h"
#include "host.h"

namespace tesseract {

// Computes and returns the dot product of the n-vectors u and v.
// Uses Intel AVX intrinsics to access the SIMD instruction set.
double DotProductAVX(const double* u, const double* v, int n) {
  int max_offset = n - 4;
  int offset = 0;
  // Accumulate a set of 4 sums in sum, by loading pairs of 4 values from u and
  // v, and multiplying them together in parallel.
  __m256d sum = _mm256_setzero_pd();
  if (offset <= max_offset) {
    offset = 4;
    // Aligned load is reputedly faster but requires 32 byte aligned input.
    if ((reinterpret_cast<const uintptr_t>(u) & 31) == 0 &&
        (reinterpret_cast<const uintptr_t>(v) & 31) == 0) {
      // Use aligned load.
      __m256d floats1 = _mm256_load_pd(u);
      __m256d floats2 = _mm256_load_pd(v);
      // Multiply.
      sum = _mm256_mul_pd(floats1, floats2);
      while (offset <= max_offset) {
        floats1 = _mm256_load_pd(u + offset);
        floats2 = _mm256_load_pd(v + offset);
        offset += 4;
        __m256d product = _mm256_mul_pd(floats1, floats2);
        sum = _mm256_add_pd(sum, product);
      }
    } else {
      // Use unaligned load.
      __m256d floats1 = _mm256_loadu_pd(u);
      __m256d floats2 = _mm256_loadu_pd(v);
      // Multiply.
      sum = _mm256_mul_pd(floats1, floats2);
      while (offset <= max_offset) {
        floats1 = _mm256_loadu_pd(u + offset);
        floats2 = _mm256_loadu_pd(v + offset);
        offset += 4;
        __m256d product = _mm256_mul_pd(floats1, floats2);
        sum = _mm256_add_pd(sum, product);
      }
    }
  }
  // Add the 4 product sums together horizontally. Not so easy as with sse, as
  // there is no add across the upper/lower 128 bit boundary, so permute to
  // move the upper 128 bits to lower in another register.
  __m256d sum2 = _mm256_permute2f128_pd(sum, sum, 1);
  sum = _mm256_hadd_pd(sum, sum2);
  sum = _mm256_hadd_pd(sum, sum);
  double result;
  // _mm256_extract_f64 doesn't exist, but resist the temptation to use an sse
  // instruction, as that introduces a 70 cycle delay. All this casting is to
  // fool the intrinsics into thinking we are extracting the bottom int64.
  auto cast_sum = _mm256_castpd_si256(sum);
  *(reinterpret_cast<int64_t*>(&result)) =
#if defined(_WIN32) || defined(__i386__)
      // This is a very simple workaround that is activated
      // for all platforms that do not have _mm256_extract_epi64.
      // _mm256_extract_epi64(X, Y) == ((uint64_t*)&X)[Y]
      ((uint64_t*)&cast_sum)[0]
#else
      _mm256_extract_epi64(cast_sum, 0)
#endif
      ;
  while (offset < n) {
    result += u[offset] * v[offset];
    ++offset;
  }
  return result;
}

}  // namespace tesseract.

#endif  // ANDROID_BUILD