X-Git-Url: https://git.sesse.net/?p=stockfish;a=blobdiff_plain;f=src%2Fnnue%2Flayers%2Faffine_transform.h;h=20ec2f1234befe5a67f6ab2d3c70c42fabac08c4;hp=ecc3008a6cc8a728927011ba4b6154a232e76994;hb=875183b310a8249922c2155e82cb4cecfae2097e;hpb=a6e89293df5af35931b61d86b6de3872a981c100;ds=sidebyside diff --git a/src/nnue/layers/affine_transform.h b/src/nnue/layers/affine_transform.h index ecc3008a..20ec2f12 100644 --- a/src/nnue/layers/affine_transform.h +++ b/src/nnue/layers/affine_transform.h @@ -104,8 +104,7 @@ namespace Eval::NNUE::Layers { __m512i sum = _mm512_setzero_si512(); const auto row = reinterpret_cast(&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])); + __m512i product = _mm512_maddubs_epi16(_mm512_loadA_si512(&input_vector[j]), _mm512_load_si512(&row[j])); product = _mm512_madd_epi16(product, kOnes); sum = _mm512_add_epi32(sum, product); } @@ -119,9 +118,7 @@ namespace Eval::NNUE::Layers { const auto iv_256 = reinterpret_cast(input); const auto row_256 = reinterpret_cast(&weights_[offset]); int j = kNumChunks * 2; - - __m256i sum256 = _mm256_maddubs_epi16( - _mm256_load_si256(&iv_256[j]), _mm256_load_si256(&row_256[j])); + __m256i sum256 = _mm256_maddubs_epi16(_mm256_loadA_si256(&iv_256[j]), _mm256_load_si256(&row_256[j])); sum256 = _mm256_madd_epi16(sum256, _mm256_set1_epi16(1)); sum256 = _mm256_hadd_epi32(sum256, sum256); sum256 = _mm256_hadd_epi32(sum256, sum256); @@ -134,8 +131,7 @@ namespace Eval::NNUE::Layers { __m256i sum = _mm256_setzero_si256(); const auto row = reinterpret_cast(&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])); + __m256i product = _mm256_maddubs_epi16(_mm256_loadA_si256(&input_vector[j]), _mm256_load_si256(&row[j])); product = _mm256_madd_epi16(product, kOnes); sum = _mm256_add_epi32(sum, product); } @@ -149,8 +145,7 @@ namespace Eval::NNUE::Layers { __m128i sum = _mm_cvtsi32_si128(biases_[i]); const auto row = reinterpret_cast(&weights_[offset]); for (IndexType j = 0; j < kNumChunks; ++j) { - __m128i product = _mm_maddubs_epi16( - _mm_load_si128(&input_vector[j]), _mm_load_si128(&row[j])); + __m128i product = _mm_maddubs_epi16(_mm_load_si128(&input_vector[j]), _mm_load_si128(&row[j])); product = _mm_madd_epi16(product, kOnes); sum = _mm_add_epi32(sum, product); }