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https://github.com/sockspls/badfish
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Simplify ClippedReLU
Removes some max calls Some speedup stats, courtesy of @AndyGrant (albeit measured in an alternate implementation) Dev 749240 nps Base 748495 nps Gain 0.100% 289936 games STC: LLR: 2.94 (-2.94,2.94) <-1.75,0.25> Total: 203040 W: 52213 L: 52179 D: 98648 Ptnml(0-2): 480, 20722, 59139, 20642, 537 https://tests.stockfishchess.org/tests/view/664805fe6dcff0d1d6b05f2c closes #5261 No functional change
This commit is contained in:
cj5716
Joost VandeVondele
parent
2d32581623
commit
27eb49a221
4 changed files with 30 additions and 39 deletions
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@ -65,41 +65,37 @@ class ClippedReLU {
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if constexpr (InputDimensions % SimdWidth == 0)
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{
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constexpr IndexType NumChunks = InputDimensions / SimdWidth;
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const __m256i Zero = _mm256_setzero_si256();
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const __m256i Offsets = _mm256_set_epi32(7, 3, 6, 2, 5, 1, 4, 0);
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const auto in = reinterpret_cast<const __m256i*>(input);
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const auto out = reinterpret_cast<__m256i*>(output);
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for (IndexType i = 0; i < NumChunks; ++i)
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{
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const __m256i words0 =
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_mm256_srai_epi16(_mm256_packs_epi32(_mm256_load_si256(&in[i * 4 + 0]),
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_mm256_load_si256(&in[i * 4 + 1])),
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_mm256_srli_epi16(_mm256_packus_epi32(_mm256_load_si256(&in[i * 4 + 0]),
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_mm256_load_si256(&in[i * 4 + 1])),
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WeightScaleBits);
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const __m256i words1 =
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_mm256_srai_epi16(_mm256_packs_epi32(_mm256_load_si256(&in[i * 4 + 2]),
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_mm256_load_si256(&in[i * 4 + 3])),
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_mm256_srli_epi16(_mm256_packus_epi32(_mm256_load_si256(&in[i * 4 + 2]),
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_mm256_load_si256(&in[i * 4 + 3])),
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WeightScaleBits);
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_mm256_store_si256(
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&out[i], _mm256_permutevar8x32_epi32(
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_mm256_max_epi8(_mm256_packs_epi16(words0, words1), Zero), Offsets));
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_mm256_store_si256(&out[i], _mm256_permutevar8x32_epi32(
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_mm256_packs_epi16(words0, words1), Offsets));
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}
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}
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else
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{
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constexpr IndexType NumChunks = InputDimensions / (SimdWidth / 2);
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const __m128i Zero = _mm_setzero_si128();
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const auto in = reinterpret_cast<const __m128i*>(input);
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const auto out = reinterpret_cast<__m128i*>(output);
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for (IndexType i = 0; i < NumChunks; ++i)
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{
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const __m128i words0 = _mm_srai_epi16(
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_mm_packs_epi32(_mm_load_si128(&in[i * 4 + 0]), _mm_load_si128(&in[i * 4 + 1])),
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const __m128i words0 = _mm_srli_epi16(
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_mm_packus_epi32(_mm_load_si128(&in[i * 4 + 0]), _mm_load_si128(&in[i * 4 + 1])),
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WeightScaleBits);
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const __m128i words1 = _mm_srai_epi16(
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_mm_packs_epi32(_mm_load_si128(&in[i * 4 + 2]), _mm_load_si128(&in[i * 4 + 3])),
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const __m128i words1 = _mm_srli_epi16(
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_mm_packus_epi32(_mm_load_si128(&in[i * 4 + 2]), _mm_load_si128(&in[i * 4 + 3])),
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WeightScaleBits);
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const __m128i packedbytes = _mm_packs_epi16(words0, words1);
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_mm_store_si128(&out[i], _mm_max_epi8(packedbytes, Zero));
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_mm_store_si128(&out[i], _mm_packs_epi16(words0, words1));
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}
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}
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constexpr IndexType Start = InputDimensions % SimdWidth == 0
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@ -109,9 +105,7 @@ class ClippedReLU {
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#elif defined(USE_SSE2)
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constexpr IndexType NumChunks = InputDimensions / SimdWidth;
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#ifdef USE_SSE41
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const __m128i Zero = _mm_setzero_si128();
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#else
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#ifndef USE_SSE41
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const __m128i k0x80s = _mm_set1_epi8(-128);
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#endif
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@ -119,6 +113,15 @@ class ClippedReLU {
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const auto out = reinterpret_cast<__m128i*>(output);
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for (IndexType i = 0; i < NumChunks; ++i)
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{
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#if defined(USE_SSE41)
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const __m128i words0 = _mm_srli_epi16(
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_mm_packus_epi32(_mm_load_si128(&in[i * 4 + 0]), _mm_load_si128(&in[i * 4 + 1])),
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WeightScaleBits);
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const __m128i words1 = _mm_srli_epi16(
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_mm_packus_epi32(_mm_load_si128(&in[i * 4 + 2]), _mm_load_si128(&in[i * 4 + 3])),
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WeightScaleBits);
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_mm_store_si128(&out[i], _mm_packs_epi16(words0, words1));
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#else
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const __m128i words0 = _mm_srai_epi16(
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_mm_packs_epi32(_mm_load_si128(&in[i * 4 + 0]), _mm_load_si128(&in[i * 4 + 1])),
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WeightScaleBits);
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@ -126,15 +129,8 @@ class ClippedReLU {
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_mm_packs_epi32(_mm_load_si128(&in[i * 4 + 2]), _mm_load_si128(&in[i * 4 + 3])),
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WeightScaleBits);
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const __m128i packedbytes = _mm_packs_epi16(words0, words1);
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_mm_store_si128(&out[i],
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#ifdef USE_SSE41
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_mm_max_epi8(packedbytes, Zero)
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#else
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_mm_subs_epi8(_mm_adds_epi8(packedbytes, k0x80s), k0x80s)
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_mm_store_si128(&out[i], _mm_subs_epi8(_mm_adds_epi8(packedbytes, k0x80s), k0x80s));
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#endif
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);
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}
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constexpr IndexType Start = NumChunks * SimdWidth;
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@ -178,14 +178,11 @@ trace(Position& pos, const Eval::NNUE::Networks& networks, Eval::NNUE::Accumulat
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ss << "| " << bucket << " ";
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ss << " | ";
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format_cp_aligned_dot(t.psqt[bucket], ss, pos);
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ss << " "
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<< " | ";
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ss << " " << " | ";
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format_cp_aligned_dot(t.positional[bucket], ss, pos);
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ss << " "
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<< " | ";
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ss << " " << " | ";
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format_cp_aligned_dot(t.psqt[bucket] + t.positional[bucket], ss, pos);
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ss << " "
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<< " |";
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ss << " " << " |";
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if (bucket == t.correctBucket)
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ss << " <-- this bucket is used";
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ss << '\n';
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@ -59,8 +59,7 @@ void make_option(OptionsMap* options, const string& n, int v, const SetRange& r)
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// Print formatted parameters, ready to be copy-pasted in Fishtest
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std::cout << n << "," << v << "," << r(v).first << "," << r(v).second << ","
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<< (r(v).second - r(v).first) / 20.0 << ","
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<< "0.0020" << std::endl;
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<< (r(v).second - r(v).first) / 20.0 << "," << "0.0020" << std::endl;
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}
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}
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@ -118,7 +117,6 @@ void Tune::Entry<Tune::PostUpdate>::read_option() {
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namespace Stockfish {
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void Tune::read_results() { /* ...insert your values here... */
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}
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void Tune::read_results() { /* ...insert your values here... */ }
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} // namespace Stockfish
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@ -286,9 +286,9 @@ void UCIEngine::bench(std::istream& args) {
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dbg_print();
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std::cerr << "\n==========================="
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<< "\nTotal time (ms) : " << elapsed << "\nNodes searched : " << nodes
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<< "\nNodes/second : " << 1000 * nodes / elapsed << std::endl;
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std::cerr << "\n===========================" << "\nTotal time (ms) : " << elapsed
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<< "\nNodes searched : " << nodes << "\nNodes/second : " << 1000 * nodes / elapsed
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<< std::endl;
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// reset callback, to not capture a dangling reference to nodesSearched
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engine.set_on_update_full([&](const auto& i) { on_update_full(i, options["UCI_ShowWDL"]); });
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