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Optimize the most common update accumalator cases w/o tiling

Browse source 
In the most common case where we only update a single state
it's faster to not use temporary accumulation registers and tiling.
(Also includes a couple of small cleanups.)

passed STC
https://tests.stockfishchess.org/tests/view/651918e3cff46e538ee0023b
LLR: 2.95 (-2.94,2.94) <0.00,2.00>
Total: 34944 W: 8989 L: 8687 D: 17268
Ptnml(0-2): 88, 3743, 9512, 4037, 92

A simpler version
https://tests.stockfishchess.org/tests/view/65190dfacff46e538ee00155
also passed but this version is stronger still
https://tests.stockfishchess.org/tests/view/6519b95fcff46e538ee00fa2

closes https://github.com/official-stockfish/Stockfish/pull/4816

No functional change
This commit is contained in:
mstembera 2023-09-30 23:12:02 -07:00 • committed by Joost VandeVondele
parent 040dfedb34
commit c17a657b04
2 changed files with 122 additions and 59 deletions
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1
src/misc.h
View file

@ -87,6 +87,7 @@ public:
void push_back(const T& value) { values_[size_++] = value; }
const T* begin() const { return values_; }
const T* end() const { return values_ + size_; }
const T& operator[](int index) const { return values_[index]; }
private:
T values_[MaxSize];

180
src/nnue/nnue_feature_transformer.h
View file

@ -370,13 +370,13 @@ namespace Stockfish::Eval::NNUE {
while (states_to_update[i] == nullptr)
--i;
StateInfo *st2 = states_to_update[i];
StateInfo* st2 = states_to_update[i];
for (; i >= 0; --i)
{
states_to_update[i]->accumulator.computed[Perspective] = true;
StateInfo* end_state = i == 0 ? computed_st : states_to_update[i - 1];
const StateInfo* end_state = i == 0 ? computed_st : states_to_update[i - 1];
for (; st2 != end_state; st2 = st2->previous)
FeatureSet::append_changed_indices<Perspective>(
@ -388,78 +388,140 @@ namespace Stockfish::Eval::NNUE {
// Now update the accumulators listed in states_to_update[], where the last element is a sentinel.
#ifdef VECTOR
for (IndexType j = 0; j < HalfDimensions / TileHeight; ++j)
if ( states_to_update[1] == nullptr
&& (removed[0].size() == 1 || removed[0].size() == 2)
&& added[0].size() == 1)
{
// Load accumulator
auto accTile = reinterpret_cast<vec_t*>(
&st->accumulator.accumulation[Perspective][j * TileHeight]);
for (IndexType k = 0; k < NumRegs; ++k)
acc[k] = vec_load(&accTile[k]);
assert(states_to_update[0]);
for (IndexType i = 0; states_to_update[i]; ++i)
{
// Difference calculation for the deactivated features
for (const auto index : removed[i])
auto accTileIn = reinterpret_cast<const vec_t*>(
&st->accumulator.accumulation[Perspective][0]);
auto accTileOut = reinterpret_cast<vec_t*>(
&states_to_update[0]->accumulator.accumulation[Perspective][0]);
const IndexType offsetR0 = HalfDimensions * removed[0][0];
auto columnR0 = reinterpret_cast<const vec_t*>(&weights[offsetR0]);
const IndexType offsetA = HalfDimensions * added[0][0];
auto columnA = reinterpret_cast<const vec_t*>(&weights[offsetA]);
if (removed[0].size() == 1)
{
const IndexType offset = HalfDimensions * index + j * TileHeight;
auto column = reinterpret_cast<const vec_t*>(&weights[offset]);
for (IndexType k = 0; k < NumRegs; ++k)
acc[k] = vec_sub_16(acc[k], column[k]);
for (IndexType k = 0; k < HalfDimensions * sizeof(std::int16_t) / sizeof(vec_t); ++k)
accTileOut[k] = vec_add_16(vec_sub_16(accTileIn[k], columnR0[k]), columnA[k]);
}
else
{
const IndexType offsetR1 = HalfDimensions * removed[0][1];
auto columnR1 = reinterpret_cast<const vec_t*>(&weights[offsetR1]);
for (IndexType k = 0; k < HalfDimensions * sizeof(std::int16_t) / sizeof(vec_t); ++k)
accTileOut[k] = vec_sub_16(
vec_add_16(accTileIn[k], columnA[k]),
vec_add_16(columnR0[k], columnR1[k]));
}
// Difference calculation for the activated features
for (const auto index : added[i])
{
const IndexType offset = HalfDimensions * index + j * TileHeight;
auto column = reinterpret_cast<const vec_t*>(&weights[offset]);
for (IndexType k = 0; k < NumRegs; ++k)
acc[k] = vec_add_16(acc[k], column[k]);
}
auto accTilePsqtIn = reinterpret_cast<const psqt_vec_t*>(
&st->accumulator.psqtAccumulation[Perspective][0]);
auto accTilePsqtOut = reinterpret_cast<psqt_vec_t*>(
&states_to_update[0]->accumulator.psqtAccumulation[Perspective][0]);
// Store accumulator
accTile = reinterpret_cast<vec_t*>(
&states_to_update[i]->accumulator.accumulation[Perspective][j * TileHeight]);
for (IndexType k = 0; k < NumRegs; ++k)
vec_store(&accTile[k], acc[k]);
}
const IndexType offsetPsqtR0 = PSQTBuckets * removed[0][0];
auto columnPsqtR0 = reinterpret_cast<const psqt_vec_t*>(&psqtWeights[offsetPsqtR0]);
const IndexType offsetPsqtA = PSQTBuckets * added[0][0];
auto columnPsqtA = reinterpret_cast<const psqt_vec_t*>(&psqtWeights[offsetPsqtA]);
if (removed[0].size() == 1)
{
for (std::size_t k = 0; k < PSQTBuckets * sizeof(std::int32_t) / sizeof(psqt_vec_t); ++k)
accTilePsqtOut[k] = vec_add_psqt_32(vec_sub_psqt_32(
accTilePsqtIn[k], columnPsqtR0[k]), columnPsqtA[k]);
}
else
{
const IndexType offsetPsqtR1 = PSQTBuckets * removed[0][1];
auto columnPsqtR1 = reinterpret_cast<const psqt_vec_t*>(&psqtWeights[offsetPsqtR1]);
for (std::size_t k = 0; k < PSQTBuckets * sizeof(std::int32_t) / sizeof(psqt_vec_t); ++k)
accTilePsqtOut[k] = vec_sub_psqt_32(
vec_add_psqt_32(accTilePsqtIn[k], columnPsqtA[k]),
vec_add_psqt_32(columnPsqtR0[k], columnPsqtR1[k]));
}
}
for (IndexType j = 0; j < PSQTBuckets / PsqtTileHeight; ++j)
else
{
// Load accumulator
auto accTilePsqt = reinterpret_cast<psqt_vec_t*>(
&st->accumulator.psqtAccumulation[Perspective][j * PsqtTileHeight]);
for (std::size_t k = 0; k < NumPsqtRegs; ++k)
psqt[k] = vec_load_psqt(&accTilePsqt[k]);
for (IndexType i = 0; states_to_update[i]; ++i)
{
// Difference calculation for the deactivated features
for (const auto index : removed[i])
for (IndexType j = 0; j < HalfDimensions / TileHeight; ++j)
{
const IndexType offset = PSQTBuckets * index + j * PsqtTileHeight;
auto columnPsqt = reinterpret_cast<const psqt_vec_t*>(&psqtWeights[offset]);
for (std::size_t k = 0; k < NumPsqtRegs; ++k)
psqt[k] = vec_sub_psqt_32(psqt[k], columnPsqt[k]);
// Load accumulator
auto accTileIn = reinterpret_cast<const vec_t*>(
&st->accumulator.accumulation[Perspective][j * TileHeight]);
for (IndexType k = 0; k < NumRegs; ++k)
acc[k] = vec_load(&accTileIn[k]);
for (IndexType i = 0; states_to_update[i]; ++i)
{
// Difference calculation for the deactivated features
for (const auto index : removed[i])
{
const IndexType offset = HalfDimensions * index + j * TileHeight;
auto column = reinterpret_cast<const vec_t*>(&weights[offset]);
for (IndexType k = 0; k < NumRegs; ++k)
acc[k] = vec_sub_16(acc[k], column[k]);
}
// Difference calculation for the activated features
for (const auto index : added[i])
{
const IndexType offset = HalfDimensions * index + j * TileHeight;
auto column = reinterpret_cast<const vec_t*>(&weights[offset]);
for (IndexType k = 0; k < NumRegs; ++k)
acc[k] = vec_add_16(acc[k], column[k]);
}
// Store accumulator
auto accTileOut = reinterpret_cast<vec_t*>(
&states_to_update[i]->accumulator.accumulation[Perspective][j * TileHeight]);
for (IndexType k = 0; k < NumRegs; ++k)
vec_store(&accTileOut[k], acc[k]);
}
}
// Difference calculation for the activated features
for (const auto index : added[i])
for (IndexType j = 0; j < PSQTBuckets / PsqtTileHeight; ++j)
{
const IndexType offset = PSQTBuckets * index + j * PsqtTileHeight;
auto columnPsqt = reinterpret_cast<const psqt_vec_t*>(&psqtWeights[offset]);
// Load accumulator
auto accTilePsqtIn = reinterpret_cast<const psqt_vec_t*>(
&st->accumulator.psqtAccumulation[Perspective][j * PsqtTileHeight]);
for (std::size_t k = 0; k < NumPsqtRegs; ++k)
psqt[k] = vec_add_psqt_32(psqt[k], columnPsqt[k]);
}
psqt[k] = vec_load_psqt(&accTilePsqtIn[k]);
// Store accumulator
accTilePsqt = reinterpret_cast<psqt_vec_t*>(
&states_to_update[i]->accumulator.psqtAccumulation[Perspective][j * PsqtTileHeight]);
for (std::size_t k = 0; k < NumPsqtRegs; ++k)
vec_store_psqt(&accTilePsqt[k], psqt[k]);
}
for (IndexType i = 0; states_to_update[i]; ++i)
{
// Difference calculation for the deactivated features
for (const auto index : removed[i])
{
const IndexType offset = PSQTBuckets * index + j * PsqtTileHeight;
auto columnPsqt = reinterpret_cast<const psqt_vec_t*>(&psqtWeights[offset]);
for (std::size_t k = 0; k < NumPsqtRegs; ++k)
psqt[k] = vec_sub_psqt_32(psqt[k], columnPsqt[k]);
}
// Difference calculation for the activated features
for (const auto index : added[i])
{
const IndexType offset = PSQTBuckets * index + j * PsqtTileHeight;
auto columnPsqt = reinterpret_cast<const psqt_vec_t*>(&psqtWeights[offset]);
for (std::size_t k = 0; k < NumPsqtRegs; ++k)
psqt[k] = vec_add_psqt_32(psqt[k], columnPsqt[k]);
}
// Store accumulator
auto accTilePsqtOut = reinterpret_cast<psqt_vec_t*>(
&states_to_update[i]->accumulator.psqtAccumulation[Perspective][j * PsqtTileHeight]);
for (std::size_t k = 0; k < NumPsqtRegs; ++k)
vec_store_psqt(&accTilePsqtOut[k], psqt[k]);
}
}
}
#else
for (IndexType i = 0; states_to_update[i]; ++i)
{