__m512i sum = _mm512_setzero_si512();
const auto row = reinterpret_cast<const __m512i*>(&weights_[offset]);
for (IndexType j = 0; j < kNumChunks; ++j) {
- __m512i product = _mm512_maddubs_epi16(
- _mm512_load_si512(&input_vector[j]), _mm512_load_si512(&row[j]));
+
+ #if defined(__MINGW32__) || defined(__MINGW64__)
+ __m512i product = _mm512_maddubs_epi16(_mm512_loadu_si512(&input_vector[j]), _mm512_load_si512(&row[j]));
+ #else
+ __m512i product = _mm512_maddubs_epi16(_mm512_load_si512(&input_vector[j]), _mm512_load_si512(&row[j]));
+ #endif
+
product = _mm512_madd_epi16(product, kOnes);
sum = _mm512_add_epi32(sum, product);
}
const auto row_256 = reinterpret_cast<const __m256i*>(&weights_[offset]);
int j = kNumChunks * 2;
- __m256i sum256 = _mm256_maddubs_epi16(
- _mm256_load_si256(&iv_256[j]), _mm256_load_si256(&row_256[j]));
+ #if defined(__MINGW32__) || defined(__MINGW64__) // See HACK comment below in AVX2.
+ __m256i sum256 = _mm256_maddubs_epi16(_mm256_loadu_si256(&iv_256[j]), _mm256_load_si256(&row_256[j]));
+ #else
+ __m256i sum256 = _mm256_maddubs_epi16(_mm256_load_si256(&iv_256[j]), _mm256_load_si256(&row_256[j]));
+ #endif
+
sum256 = _mm256_madd_epi16(sum256, _mm256_set1_epi16(1));
sum256 = _mm256_hadd_epi32(sum256, sum256);
sum256 = _mm256_hadd_epi32(sum256, sum256);
const auto row = reinterpret_cast<const __m256i*>(&weights_[offset]);
for (IndexType j = 0; j < kNumChunks; ++j) {
__m256i product = _mm256_maddubs_epi16(
- _mm256_load_si256(&input_vector[j]), _mm256_load_si256(&row[j]));
+
+ #if defined(__MINGW32__) || defined(__MINGW64__)
+ // HACK: Use _mm256_loadu_si256() instead of _mm256_load_si256. Because the binary
+ // compiled with g++ in MSYS2 crashes here because the output memory is not aligned
+ // even though alignas is specified.
+ _mm256_loadu_si256
+ #else
+ _mm256_load_si256
+ #endif
+
+ (&input_vector[j]), _mm256_load_si256(&row[j]));
product = _mm256_madd_epi16(product, kOnes);
sum = _mm256_add_epi32(sum, product);
}
const auto out = reinterpret_cast<__m256i*>(output);
for (IndexType i = 0; i < kNumChunks; ++i) {
const __m256i words0 = _mm256_srai_epi16(_mm256_packs_epi32(
- _mm256_load_si256(&in[i * 4 + 0]),
- _mm256_load_si256(&in[i * 4 + 1])), kWeightScaleBits);
+
+ #if defined(__MINGW32__) || defined(__MINGW64__)
+ // HACK: Use _mm256_loadu_si256() instead of _mm256_load_si256. Because the binary
+ // compiled with g++ in MSYS2 crashes here because the output memory is not aligned
+ // even though alignas is specified.
+ _mm256_loadu_si256
+ #else
+ _mm256_load_si256
+ #endif
+
+ (&in[i * 4 + 0]),
+
+ #if defined(__MINGW32__) || defined(__MINGW64__)
+ _mm256_loadu_si256
+ #else
+ _mm256_load_si256
+ #endif
+
+ (&in[i * 4 + 1])), kWeightScaleBits);
const __m256i words1 = _mm256_srai_epi16(_mm256_packs_epi32(
- _mm256_load_si256(&in[i * 4 + 2]),
- _mm256_load_si256(&in[i * 4 + 3])), kWeightScaleBits);
- _mm256_store_si256(
- &out[i], _mm256_permutevar8x32_epi32(_mm256_max_epi8(
+
+ #if defined(__MINGW32__) || defined(__MINGW64__)
+ _mm256_loadu_si256
+ #else
+ _mm256_load_si256
+ #endif
+
+ (&in[i * 4 + 2]),
+
+ #if defined(__MINGW32__) || defined(__MINGW64__)
+ _mm256_loadu_si256
+ #else
+ _mm256_load_si256
+ #endif
+
+ (&in[i * 4 + 3])), kWeightScaleBits);
+
+ #if defined(__MINGW32__) || defined(__MINGW64__)
+ _mm256_storeu_si256
+ #else
+ _mm256_store_si256
+ #endif
+
+ (&out[i], _mm256_permutevar8x32_epi32(_mm256_max_epi8(
_mm256_packs_epi16(words0, words1), kZero), kOffsets));
}
constexpr IndexType kStart = kNumChunks * kSimdWidth;
auto out = reinterpret_cast<__m256i*>(&output[offset]);
for (IndexType j = 0; j < kNumChunks; ++j) {
__m256i sum0 =
- _mm256_load_si256(&reinterpret_cast<const __m256i*>(
+
+ #if defined(__MINGW32__) || defined(__MINGW64__)
+ // HACK: Use _mm256_loadu_si256() instead of _mm256_load_si256. Because the binary
+ // compiled with g++ in MSYS2 crashes here because the output memory is not aligned
+ // even though alignas is specified.
+ _mm256_loadu_si256
+ #else
+ _mm256_load_si256
+ #endif
+
+ (&reinterpret_cast<const __m256i*>(
accumulation[perspectives[p]][0])[j * 2 + 0]);
__m256i sum1 =
- _mm256_load_si256(&reinterpret_cast<const __m256i*>(
+
+ #if defined(__MINGW32__) || defined(__MINGW64__)
+ _mm256_loadu_si256
+ #else
+ _mm256_load_si256
+ #endif
+
+ (&reinterpret_cast<const __m256i*>(
accumulation[perspectives[p]][0])[j * 2 + 1]);
- _mm256_store_si256(&out[j], _mm256_permute4x64_epi64(_mm256_max_epi8(
+
+ #if defined(__MINGW32__) || defined(__MINGW64__)
+ _mm256_storeu_si256
+ #else
+ _mm256_store_si256
+ #endif
+
+ (&out[j], _mm256_permute4x64_epi64(_mm256_max_epi8(
_mm256_packs_epi16(sum0, sum1), kZero), kControl));
}
auto column = reinterpret_cast<const __m256i*>(&weights_[offset]);
constexpr IndexType kNumChunks = kHalfDimensions / (kSimdWidth / 2);
for (IndexType j = 0; j < kNumChunks; ++j) {
+ #if defined(__MINGW32__) || defined(__MINGW64__)
+ _mm256_storeu_si256(&accumulation[j], _mm256_add_epi16(_mm256_loadu_si256(&accumulation[j]), column[j]));
+ #else
accumulation[j] = _mm256_add_epi16(accumulation[j], column[j]);
+ #endif
}
#elif defined(USE_SSE2)