X-Git-Url: https://git.sesse.net/?a=blobdiff_plain;f=src%2Fnnue%2Fnnue_feature_transformer.h;h=34d7292c0065eb0b392d3062bfe3118bbc441fca;hb=f7d1491b3df28bf10faac81e340cb6a22fc5b57b;hp=f4024dce83b9d1e5f02ce87528a80d70a68874fc;hpb=ad926d34c0105d523bfa5cb92cbcf9f337d54c08;p=stockfish diff --git a/src/nnue/nnue_feature_transformer.h b/src/nnue/nnue_feature_transformer.h index f4024dce..34d7292c 100644 --- a/src/nnue/nnue_feature_transformer.h +++ b/src/nnue/nnue_feature_transformer.h @@ -47,12 +47,22 @@ namespace Stockfish::Eval::NNUE { #define vec_store(a,b) _mm512_store_si512(a,b) #define vec_add_16(a,b) _mm512_add_epi16(a,b) #define vec_sub_16(a,b) _mm512_sub_epi16(a,b) + #define vec_mul_16(a,b) _mm512_mullo_epi16(a,b) + #define vec_zero() _mm512_setzero_epi32() + #define vec_set_16(a) _mm512_set1_epi16(a) + #define vec_max_16(a,b) _mm512_max_epi16(a,b) + #define vec_min_16(a,b) _mm512_min_epi16(a,b) + inline vec_t vec_msb_pack_16(vec_t a, vec_t b){ + vec_t compacted = _mm512_packs_epi16(_mm512_srli_epi16(a,7),_mm512_srli_epi16(b,7)); + return _mm512_permutexvar_epi64(_mm512_setr_epi64(0, 2, 4, 6, 1, 3, 5, 7), compacted); + } #define vec_load_psqt(a) _mm256_load_si256(a) #define vec_store_psqt(a,b) _mm256_store_si256(a,b) #define vec_add_psqt_32(a,b) _mm256_add_epi32(a,b) #define vec_sub_psqt_32(a,b) _mm256_sub_epi32(a,b) #define vec_zero_psqt() _mm256_setzero_si256() #define NumRegistersSIMD 32 + #define MaxChunkSize 64 #elif USE_AVX2 typedef __m256i vec_t; @@ -61,12 +71,22 @@ namespace Stockfish::Eval::NNUE { #define vec_store(a,b) _mm256_store_si256(a,b) #define vec_add_16(a,b) _mm256_add_epi16(a,b) #define vec_sub_16(a,b) _mm256_sub_epi16(a,b) + #define vec_mul_16(a,b) _mm256_mullo_epi16(a,b) + #define vec_zero() _mm256_setzero_si256() + #define vec_set_16(a) _mm256_set1_epi16(a) + #define vec_max_16(a,b) _mm256_max_epi16(a,b) + #define vec_min_16(a,b) _mm256_min_epi16(a,b) + inline vec_t vec_msb_pack_16(vec_t a, vec_t b){ + vec_t compacted = _mm256_packs_epi16(_mm256_srli_epi16(a,7), _mm256_srli_epi16(b,7)); + return _mm256_permute4x64_epi64(compacted, 0b11011000); + } #define vec_load_psqt(a) _mm256_load_si256(a) #define vec_store_psqt(a,b) _mm256_store_si256(a,b) #define vec_add_psqt_32(a,b) _mm256_add_epi32(a,b) #define vec_sub_psqt_32(a,b) _mm256_sub_epi32(a,b) #define vec_zero_psqt() _mm256_setzero_si256() #define NumRegistersSIMD 16 + #define MaxChunkSize 32 #elif USE_SSE2 typedef __m128i vec_t; @@ -75,12 +95,19 @@ namespace Stockfish::Eval::NNUE { #define vec_store(a,b) *(a)=(b) #define vec_add_16(a,b) _mm_add_epi16(a,b) #define vec_sub_16(a,b) _mm_sub_epi16(a,b) + #define vec_mul_16(a,b) _mm_mullo_epi16(a,b) + #define vec_zero() _mm_setzero_si128() + #define vec_set_16(a) _mm_set1_epi16(a) + #define vec_max_16(a,b) _mm_max_epi16(a,b) + #define vec_min_16(a,b) _mm_min_epi16(a,b) + #define vec_msb_pack_16(a,b) _mm_packs_epi16(_mm_srli_epi16(a,7),_mm_srli_epi16(b,7)) #define vec_load_psqt(a) (*(a)) #define vec_store_psqt(a,b) *(a)=(b) #define vec_add_psqt_32(a,b) _mm_add_epi32(a,b) #define vec_sub_psqt_32(a,b) _mm_sub_epi32(a,b) #define vec_zero_psqt() _mm_setzero_si128() #define NumRegistersSIMD (Is64Bit ? 16 : 8) + #define MaxChunkSize 16 #elif USE_MMX typedef __m64 vec_t; @@ -89,12 +116,26 @@ namespace Stockfish::Eval::NNUE { #define vec_store(a,b) *(a)=(b) #define vec_add_16(a,b) _mm_add_pi16(a,b) #define vec_sub_16(a,b) _mm_sub_pi16(a,b) + #define vec_mul_16(a,b) _mm_mullo_pi16(a,b) + #define vec_zero() _mm_setzero_si64() + #define vec_set_16(a) _mm_set1_pi16(a) + inline vec_t vec_max_16(vec_t a,vec_t b){ + vec_t comparison = _mm_cmpgt_pi16(a,b); + return _mm_or_si64(_mm_and_si64(comparison, a), _mm_andnot_si64(comparison, b)); + } + inline vec_t vec_min_16(vec_t a,vec_t b){ + vec_t comparison = _mm_cmpgt_pi16(a,b); + return _mm_or_si64(_mm_and_si64(comparison, b), _mm_andnot_si64(comparison, a)); + } + #define vec_msb_pack_16(a,b) _mm_packs_pi16(_mm_srli_pi16(a,7),_mm_srli_pi16(b,7)) #define vec_load_psqt(a) (*(a)) #define vec_store_psqt(a,b) *(a)=(b) #define vec_add_psqt_32(a,b) _mm_add_pi32(a,b) #define vec_sub_psqt_32(a,b) _mm_sub_pi32(a,b) #define vec_zero_psqt() _mm_setzero_si64() + #define vec_cleanup() _mm_empty() #define NumRegistersSIMD 8 + #define MaxChunkSize 8 #elif USE_NEON typedef int16x8_t vec_t; @@ -103,12 +144,24 @@ namespace Stockfish::Eval::NNUE { #define vec_store(a,b) *(a)=(b) #define vec_add_16(a,b) vaddq_s16(a,b) #define vec_sub_16(a,b) vsubq_s16(a,b) + #define vec_mul_16(a,b) vmulq_s16(a,b) + #define vec_zero() vec_t{0} + #define vec_set_16(a) vdupq_n_s16(a) + #define vec_max_16(a,b) vmaxq_s16(a,b) + #define vec_min_16(a,b) vminq_s16(a,b) + inline vec_t vec_msb_pack_16(vec_t a, vec_t b){ + const int8x8_t shifta = vshrn_n_s16(a, 7); + const int8x8_t shiftb = vshrn_n_s16(b, 7); + const int8x16_t compacted = vcombine_s8(shifta,shiftb); + return *reinterpret_cast (&compacted); + } #define vec_load_psqt(a) (*(a)) #define vec_store_psqt(a,b) *(a)=(b) #define vec_add_psqt_32(a,b) vaddq_s32(a,b) #define vec_sub_psqt_32(a,b) vsubq_s32(a,b) #define vec_zero_psqt() psqt_vec_t{0} #define NumRegistersSIMD 16 + #define MaxChunkSize 16 #else #undef VECTOR @@ -123,8 +176,10 @@ namespace Stockfish::Eval::NNUE { // We use __m* types as template arguments, which causes GCC to emit warnings // about losing some attribute information. This is irrelevant to us as we // only take their size, so the following pragma are harmless. + #if defined(__GNUC__) #pragma GCC diagnostic push #pragma GCC diagnostic ignored "-Wignored-attributes" + #endif template (); static constexpr int NumPsqtRegs = BestRegisterCount(); - + #if defined(__GNUC__) #pragma GCC diagnostic pop - + #endif #endif @@ -183,7 +238,7 @@ namespace Stockfish::Eval::NNUE { // Number of input/output dimensions static constexpr IndexType InputDimensions = FeatureSet::Dimensions; - static constexpr IndexType OutputDimensions = HalfDimensions * 2; + static constexpr IndexType OutputDimensions = HalfDimensions; // Size of forward propagation buffer static constexpr std::size_t BufferSize = @@ -191,7 +246,7 @@ namespace Stockfish::Eval::NNUE { // Hash value embedded in the evaluation file static constexpr std::uint32_t get_hash_value() { - return FeatureSet::HashValue ^ OutputDimensions; + return FeatureSet::HashValue ^ (OutputDimensions * 2); } // Read network parameters @@ -229,143 +284,55 @@ namespace Stockfish::Eval::NNUE { ) / 2; - #if defined(USE_AVX512) - - constexpr IndexType NumChunks = HalfDimensions / (SimdWidth * 2); - static_assert(HalfDimensions % (SimdWidth * 2) == 0); - const __m512i Control = _mm512_setr_epi64(0, 2, 4, 6, 1, 3, 5, 7); - const __m512i Zero = _mm512_setzero_si512(); - for (IndexType p = 0; p < 2; ++p) { - const IndexType offset = HalfDimensions * p; - auto out = reinterpret_cast<__m512i*>(&output[offset]); - for (IndexType j = 0; j < NumChunks; ++j) - { - __m512i sum0 = _mm512_load_si512(&reinterpret_cast - (accumulation[perspectives[p]])[j * 2 + 0]); - __m512i sum1 = _mm512_load_si512(&reinterpret_cast - (accumulation[perspectives[p]])[j * 2 + 1]); + const IndexType offset = (HalfDimensions / 2) * p; - _mm512_store_si512(&out[j], _mm512_permutexvar_epi64(Control, - _mm512_max_epi8(_mm512_packs_epi16(sum0, sum1), Zero))); - } - } - return psqt; +#if defined(VECTOR) - #elif defined(USE_AVX2) + constexpr IndexType OutputChunkSize = MaxChunkSize; + static_assert((HalfDimensions / 2) % OutputChunkSize == 0); + constexpr IndexType NumOutputChunks = HalfDimensions / 2 / OutputChunkSize; - constexpr IndexType NumChunks = HalfDimensions / SimdWidth; - constexpr int Control = 0b11011000; - const __m256i Zero = _mm256_setzero_si256(); + vec_t Zero = vec_zero(); + vec_t One = vec_set_16(127); - for (IndexType p = 0; p < 2; ++p) - { - const IndexType offset = HalfDimensions * p; - auto out = reinterpret_cast<__m256i*>(&output[offset]); - for (IndexType j = 0; j < NumChunks; ++j) - { - __m256i sum0 = _mm256_load_si256(&reinterpret_cast - (accumulation[perspectives[p]])[j * 2 + 0]); - __m256i sum1 = _mm256_load_si256(&reinterpret_cast - (accumulation[perspectives[p]])[j * 2 + 1]); + const vec_t* in0 = reinterpret_cast(&(accumulation[perspectives[p]][0])); + const vec_t* in1 = reinterpret_cast(&(accumulation[perspectives[p]][HalfDimensions / 2])); + vec_t* out = reinterpret_cast< vec_t*>(output + offset); - _mm256_store_si256(&out[j], _mm256_permute4x64_epi64( - _mm256_max_epi8(_mm256_packs_epi16(sum0, sum1), Zero), Control)); - } - } - return psqt; - - #elif defined(USE_SSE2) - - #ifdef USE_SSE41 - constexpr IndexType NumChunks = HalfDimensions / SimdWidth; - const __m128i Zero = _mm_setzero_si128(); - #else - constexpr IndexType NumChunks = HalfDimensions / SimdWidth; - const __m128i k0x80s = _mm_set1_epi8(-128); - #endif - - for (IndexType p = 0; p < 2; ++p) - { - const IndexType offset = HalfDimensions * p; - auto out = reinterpret_cast<__m128i*>(&output[offset]); - for (IndexType j = 0; j < NumChunks; ++j) + for (IndexType j = 0; j < NumOutputChunks; j += 1) { - __m128i sum0 = _mm_load_si128(&reinterpret_cast - (accumulation[perspectives[p]])[j * 2 + 0]); - __m128i sum1 = _mm_load_si128(&reinterpret_cast - (accumulation[perspectives[p]])[j * 2 + 1]); - const __m128i packedbytes = _mm_packs_epi16(sum0, sum1); - - #ifdef USE_SSE41 - _mm_store_si128(&out[j], _mm_max_epi8(packedbytes, Zero)); - #else - _mm_store_si128(&out[j], _mm_subs_epi8(_mm_adds_epi8(packedbytes, k0x80s), k0x80s)); - #endif - } - } - return psqt; + const vec_t sum0a = vec_max_16(vec_min_16(in0[j * 2 + 0], One), Zero); + const vec_t sum0b = vec_max_16(vec_min_16(in0[j * 2 + 1], One), Zero); + const vec_t sum1a = vec_max_16(vec_min_16(in1[j * 2 + 0], One), Zero); + const vec_t sum1b = vec_max_16(vec_min_16(in1[j * 2 + 1], One), Zero); - #elif defined(USE_MMX) + const vec_t pa = vec_mul_16(sum0a, sum1a); + const vec_t pb = vec_mul_16(sum0b, sum1b); - constexpr IndexType NumChunks = HalfDimensions / SimdWidth; - const __m64 k0x80s = _mm_set1_pi8(-128); - - for (IndexType p = 0; p < 2; ++p) - { - const IndexType offset = HalfDimensions * p; - auto out = reinterpret_cast<__m64*>(&output[offset]); - for (IndexType j = 0; j < NumChunks; ++j) - { - __m64 sum0 = *(&reinterpret_cast(accumulation[perspectives[p]])[j * 2 + 0]); - __m64 sum1 = *(&reinterpret_cast(accumulation[perspectives[p]])[j * 2 + 1]); - const __m64 packedbytes = _mm_packs_pi16(sum0, sum1); - out[j] = _mm_subs_pi8(_mm_adds_pi8(packedbytes, k0x80s), k0x80s); + out[j] = vec_msb_pack_16(pa, pb); } - } - _mm_empty(); - return psqt; - - #elif defined(USE_NEON) - - constexpr IndexType NumChunks = HalfDimensions / (SimdWidth / 2); - const int8x8_t Zero = {0}; - - for (IndexType p = 0; p < 2; ++p) - { - const IndexType offset = HalfDimensions * p; - const auto out = reinterpret_cast(&output[offset]); - constexpr IndexType UnrollFactor = 16; - static_assert(UnrollFactor % UnrollFactor == 0); - for (IndexType j = 0; j < NumChunks; j += UnrollFactor) - { - int16x8_t sums[UnrollFactor]; - for (IndexType i = 0; i < UnrollFactor; ++i) - sums[i] = reinterpret_cast(accumulation[perspectives[p]])[j+i]; +#else - for (IndexType i = 0; i < UnrollFactor; ++i) - out[j+i] = vmax_s8(vqmovn_s16(sums[i]), Zero); + for (IndexType j = 0; j < HalfDimensions / 2; ++j) { + BiasType sum0 = accumulation[static_cast(perspectives[p])][j + 0]; + BiasType sum1 = accumulation[static_cast(perspectives[p])][j + HalfDimensions / 2]; + sum0 = std::max(0, std::min(127, sum0)); + sum1 = std::max(0, std::min(127, sum1)); + output[offset + j] = static_cast(sum0 * sum1 / 128); } + +#endif } - return psqt; - #else +#if defined(vec_cleanup) + vec_cleanup(); +#endif - for (IndexType p = 0; p < 2; ++p) - { - const IndexType offset = HalfDimensions * p; - for (IndexType j = 0; j < HalfDimensions; ++j) - { - BiasType sum = accumulation[perspectives[p]][j]; - output[offset + j] = static_cast(std::max(0, std::min(127, sum))); - } - } return psqt; - #endif - } // end of function transform()