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https://github.com/sockspls/badfish
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Workaround using unaligned loads for gcc < 9
despite usage of alignas, the generated (avx2/avx512) code with older compilers needs to use unaligned loads with older gcc (e.g. confirmed crash with gcc 7.3/mingw on abrok). Better performance thus requires gcc >= 9 on hardware supporting avx2/avx512 closes https://github.com/official-stockfish/Stockfish/pull/2969 No functional change
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a54f9011c3
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4 changed files with 36 additions and 107 deletions
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@ -104,13 +104,7 @@ namespace Eval::NNUE::Layers {
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__m512i sum = _mm512_setzero_si512();
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const auto row = reinterpret_cast<const __m512i*>(&weights_[offset]);
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for (IndexType j = 0; j < kNumChunks; ++j) {
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#if defined(__MINGW32__) || defined(__MINGW64__)
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__m512i product = _mm512_maddubs_epi16(_mm512_loadu_si512(&input_vector[j]), _mm512_load_si512(&row[j]));
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#else
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__m512i product = _mm512_maddubs_epi16(_mm512_load_si512(&input_vector[j]), _mm512_load_si512(&row[j]));
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#endif
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__m512i product = _mm512_maddubs_epi16(_mm512_loadA_si512(&input_vector[j]), _mm512_load_si512(&row[j]));
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product = _mm512_madd_epi16(product, kOnes);
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sum = _mm512_add_epi32(sum, product);
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}
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@ -124,13 +118,7 @@ namespace Eval::NNUE::Layers {
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const auto iv_256 = reinterpret_cast<const __m256i*>(input);
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const auto row_256 = reinterpret_cast<const __m256i*>(&weights_[offset]);
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int j = kNumChunks * 2;
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#if defined(__MINGW32__) || defined(__MINGW64__) // See HACK comment below in AVX2.
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__m256i sum256 = _mm256_maddubs_epi16(_mm256_loadu_si256(&iv_256[j]), _mm256_load_si256(&row_256[j]));
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#else
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__m256i sum256 = _mm256_maddubs_epi16(_mm256_load_si256(&iv_256[j]), _mm256_load_si256(&row_256[j]));
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#endif
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__m256i sum256 = _mm256_maddubs_epi16(_mm256_loadA_si256(&iv_256[j]), _mm256_load_si256(&row_256[j]));
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sum256 = _mm256_madd_epi16(sum256, _mm256_set1_epi16(1));
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sum256 = _mm256_hadd_epi32(sum256, sum256);
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sum256 = _mm256_hadd_epi32(sum256, sum256);
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@ -143,18 +131,7 @@ namespace Eval::NNUE::Layers {
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__m256i sum = _mm256_setzero_si256();
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const auto row = reinterpret_cast<const __m256i*>(&weights_[offset]);
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for (IndexType j = 0; j < kNumChunks; ++j) {
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__m256i product = _mm256_maddubs_epi16(
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#if defined(__MINGW32__) || defined(__MINGW64__)
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// HACK: Use _mm256_loadu_si256() instead of _mm256_load_si256. Because the binary
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// compiled with g++ in MSYS2 crashes here because the output memory is not aligned
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// even though alignas is specified.
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_mm256_loadu_si256
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#else
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_mm256_load_si256
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#endif
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(&input_vector[j]), _mm256_load_si256(&row[j]));
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__m256i product = _mm256_maddubs_epi16(_mm256_loadA_si256(&input_vector[j]), _mm256_load_si256(&row[j]));
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product = _mm256_madd_epi16(product, kOnes);
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sum = _mm256_add_epi32(sum, product);
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}
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@ -168,8 +145,7 @@ namespace Eval::NNUE::Layers {
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__m128i sum = _mm_cvtsi32_si128(biases_[i]);
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const auto row = reinterpret_cast<const __m128i*>(&weights_[offset]);
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for (IndexType j = 0; j < kNumChunks; ++j) {
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__m128i product = _mm_maddubs_epi16(
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_mm_load_si128(&input_vector[j]), _mm_load_si128(&row[j]));
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__m128i product = _mm_maddubs_epi16(_mm_load_si128(&input_vector[j]), _mm_load_si128(&row[j]));
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product = _mm_madd_epi16(product, kOnes);
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sum = _mm_add_epi32(sum, product);
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}
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@ -74,50 +74,12 @@ namespace Eval::NNUE::Layers {
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const auto out = reinterpret_cast<__m256i*>(output);
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for (IndexType i = 0; i < kNumChunks; ++i) {
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const __m256i words0 = _mm256_srai_epi16(_mm256_packs_epi32(
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#if defined(__MINGW32__) || defined(__MINGW64__)
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// HACK: Use _mm256_loadu_si256() instead of _mm256_load_si256. Because the binary
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// compiled with g++ in MSYS2 crashes here because the output memory is not aligned
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// even though alignas is specified.
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_mm256_loadu_si256
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#else
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_mm256_load_si256
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#endif
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(&in[i * 4 + 0]),
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#if defined(__MINGW32__) || defined(__MINGW64__)
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_mm256_loadu_si256
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#else
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_mm256_load_si256
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#endif
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(&in[i * 4 + 1])), kWeightScaleBits);
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_mm256_loadA_si256(&in[i * 4 + 0]),
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_mm256_loadA_si256(&in[i * 4 + 1])), kWeightScaleBits);
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const __m256i words1 = _mm256_srai_epi16(_mm256_packs_epi32(
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#if defined(__MINGW32__) || defined(__MINGW64__)
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_mm256_loadu_si256
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#else
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_mm256_load_si256
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#endif
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(&in[i * 4 + 2]),
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#if defined(__MINGW32__) || defined(__MINGW64__)
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_mm256_loadu_si256
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#else
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_mm256_load_si256
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#endif
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(&in[i * 4 + 3])), kWeightScaleBits);
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#if defined(__MINGW32__) || defined(__MINGW64__)
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_mm256_storeu_si256
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#else
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_mm256_store_si256
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#endif
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(&out[i], _mm256_permutevar8x32_epi32(_mm256_max_epi8(
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_mm256_loadA_si256(&in[i * 4 + 2]),
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_mm256_loadA_si256(&in[i * 4 + 3])), kWeightScaleBits);
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_mm256_storeA_si256(&out[i], _mm256_permutevar8x32_epi32(_mm256_max_epi8(
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_mm256_packs_epi16(words0, words1), kZero), kOffsets));
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}
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constexpr IndexType kStart = kNumChunks * kSimdWidth;
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@ -37,6 +37,27 @@
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#include <arm_neon.h>
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#endif
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// HACK: Use _mm256_loadu_si256() instead of _mm256_load_si256. Otherwise a binary
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// compiled with older g++ crashes because the output memory is not aligned
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// even though alignas is specified.
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#if defined(USE_AVX2)
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#if defined(__GNUC__ ) && (__GNUC__ < 9)
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#define _mm256_loadA_si256 _mm256_loadu_si256
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#define _mm256_storeA_si256 _mm256_storeu_si256
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#else
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#define _mm256_loadA_si256 _mm256_load_si256
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#define _mm256_storeA_si256 _mm256_store_si256
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#endif
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#endif
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#if defined(USE_AVX512)
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#if defined(__GNUC__ ) && (__GNUC__ < 9)
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#define _mm512_loadA_si512 _mm512_loadu_si512
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#else
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#define _mm512_loadA_si512 _mm512_load_si512
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#endif
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#endif
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namespace Eval::NNUE {
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// Version of the evaluation file
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@ -109,37 +109,11 @@ namespace Eval::NNUE {
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#if defined(USE_AVX2)
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auto out = reinterpret_cast<__m256i*>(&output[offset]);
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for (IndexType j = 0; j < kNumChunks; ++j) {
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__m256i sum0 =
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#if defined(__MINGW32__) || defined(__MINGW64__)
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// HACK: Use _mm256_loadu_si256() instead of _mm256_load_si256. Because the binary
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// compiled with g++ in MSYS2 crashes here because the output memory is not aligned
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// even though alignas is specified.
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_mm256_loadu_si256
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#else
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_mm256_load_si256
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#endif
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(&reinterpret_cast<const __m256i*>(
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accumulation[perspectives[p]][0])[j * 2 + 0]);
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__m256i sum1 =
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#if defined(__MINGW32__) || defined(__MINGW64__)
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_mm256_loadu_si256
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#else
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_mm256_load_si256
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#endif
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(&reinterpret_cast<const __m256i*>(
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accumulation[perspectives[p]][0])[j * 2 + 1]);
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#if defined(__MINGW32__) || defined(__MINGW64__)
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_mm256_storeu_si256
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#else
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_mm256_store_si256
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#endif
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(&out[j], _mm256_permute4x64_epi64(_mm256_max_epi8(
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__m256i sum0 = _mm256_loadA_si256(
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&reinterpret_cast<const __m256i*>(accumulation[perspectives[p]][0])[j * 2 + 0]);
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__m256i sum1 = _mm256_loadA_si256(
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&reinterpret_cast<const __m256i*>(accumulation[perspectives[p]][0])[j * 2 + 1]);
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_mm256_storeA_si256(&out[j], _mm256_permute4x64_epi64(_mm256_max_epi8(
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_mm256_packs_epi16(sum0, sum1), kZero), kControl));
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}
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@ -202,11 +176,7 @@ namespace Eval::NNUE {
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auto column = reinterpret_cast<const __m256i*>(&weights_[offset]);
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constexpr IndexType kNumChunks = kHalfDimensions / (kSimdWidth / 2);
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for (IndexType j = 0; j < kNumChunks; ++j) {
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#if defined(__MINGW32__) || defined(__MINGW64__)
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_mm256_storeu_si256(&accumulation[j], _mm256_add_epi16(_mm256_loadu_si256(&accumulation[j]), column[j]));
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#else
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accumulation[j] = _mm256_add_epi16(accumulation[j], column[j]);
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#endif
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_mm256_storeA_si256(&accumulation[j], _mm256_add_epi16(_mm256_loadA_si256(&accumulation[j]), column[j]));
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}
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#elif defined(USE_SSE2)
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