jirayu_sri/stockfish
1
0
Fork 0
mirror of https://github.com/official-stockfish/Stockfish.git synced 2026-07-22 12:47:08 +00:00
Code Issues Packages Projects Releases Wiki Activity

Simplify and refactor clipped_relu.h

Browse Source 
remove AVX2 special casing

based on earlier https://github.com/official-stockfish/Stockfish/pull/6824 that passed non-regression STC:
LLR: 3.56 (-2.94,2.94) <-1.75,0.25>
Total: 49888 W: 12683 L: 12439 D: 24766
Ptnml(0-2): 104, 5170, 14153, 5412, 105
https://tests.stockfishchess.org/tests/view/6a0702c58d9bd4cd7cd69462

No change on non-AVX2 architectures.

closes https://github.com/official-stockfish/Stockfish/pull/6825

No functional change
This commit is contained in:
Myself
2026-05-17 20:50:22 +02:00
committed by Joost VandeVondele
parent d6469b3980
commit 3fcd374ad4
1 changed files with 3 additions and 43 deletions
Download Patch File Download Diff File Expand all files Collapse all files
src/nnue/layers/clipped_relu.h
+3 -43
View File
@@ -67,49 +67,9 @@ class ClippedReLU {
// Forward propagation
void propagate(const InputType* input, OutputType* output) const {
#if defined(USE_AVX2)
if constexpr (InputDimensions % SimdWidth == 0)
{
constexpr IndexType NumChunks = InputDimensions / SimdWidth;
const __m256i Offsets = _mm256_set_epi32(7, 3, 6, 2, 5, 1, 4, 0);
const auto in = reinterpret_cast<const __m256i*>(input);
const auto out = reinterpret_cast<__m256i*>(output);
for (IndexType i = 0; i < NumChunks; ++i)
{
const __m256i words0 =
_mm256_srli_epi16(_mm256_packus_epi32(_mm256_load_si256(&in[i * 4 + 0]),
_mm256_load_si256(&in[i * 4 + 1])),
WeightScaleBits);
const __m256i words1 =
_mm256_srli_epi16(_mm256_packus_epi32(_mm256_load_si256(&in[i * 4 + 2]),
_mm256_load_si256(&in[i * 4 + 3])),
WeightScaleBits);
_mm256_store_si256(&out[i], _mm256_permutevar8x32_epi32(
_mm256_packs_epi16(words0, words1), Offsets));
}
}
else
{
constexpr IndexType NumChunks = InputDimensions / (SimdWidth / 2);
const auto in = reinterpret_cast<const __m128i*>(input);
const auto out = reinterpret_cast<__m128i*>(output);
for (IndexType i = 0; i < NumChunks; ++i)
{
const __m128i words0 = _mm_srli_epi16(
_mm_packus_epi32(_mm_load_si128(&in[i * 4 + 0]), _mm_load_si128(&in[i * 4 + 1])),
WeightScaleBits);
const __m128i words1 = _mm_srli_epi16(
_mm_packus_epi32(_mm_load_si128(&in[i * 4 + 2]), _mm_load_si128(&in[i * 4 + 3])),
WeightScaleBits);
_mm_store_si128(&out[i], _mm_packs_epi16(words0, words1));
}
}
constexpr IndexType Start = InputDimensions % SimdWidth == 0
? InputDimensions / SimdWidth * SimdWidth
: InputDimensions / (SimdWidth / 2) * (SimdWidth / 2);
#elif defined(USE_SSE2)
constexpr IndexType NumChunks = InputDimensions / SimdWidth;
#if defined(USE_SSE2)
constexpr IndexType NumChunks = InputDimensions / 16;
#ifndef USE_SSE41
const __m128i k0x80s = _mm_set1_epi8(-128);
@@ -138,7 +98,7 @@ class ClippedReLU {
_mm_store_si128(&out[i], _mm_subs_epi8(_mm_adds_epi8(packedbytes, k0x80s), k0x80s));
#endif
}
constexpr IndexType Start = NumChunks * SimdWidth;
constexpr IndexType Start = NumChunks * 16;
#elif defined(USE_NEON)
constexpr IndexType NumChunks = InputDimensions / (SimdWidth / 2);