template <typename Derived>
class FeatureSetBase {
- public:
- // Get a list of indices for active features
- template <typename IndexListType>
- static void AppendActiveIndices(
- const Position& pos, TriggerEvent trigger, IndexListType active[2]) {
-
- for (Color perspective : { WHITE, BLACK }) {
- Derived::CollectActiveIndices(
- pos, trigger, perspective, &active[perspective]);
- }
- }
-
- // Get a list of indices for recently changed features
- template <typename PositionType, typename IndexListType>
- static void AppendChangedIndices(
- const PositionType& pos, TriggerEvent trigger,
- IndexListType removed[2], IndexListType added[2], bool reset[2]) {
-
- auto collect_for_one = [&](const DirtyPiece& dp) {
- for (Color perspective : { WHITE, BLACK }) {
- switch (trigger) {
- case TriggerEvent::kFriendKingMoved:
- reset[perspective] = dp.piece[0] == make_piece(perspective, KING);
- break;
- default:
- assert(false);
- break;
- }
- if (reset[perspective]) {
- Derived::CollectActiveIndices(
- pos, trigger, perspective, &added[perspective]);
- } else {
- Derived::CollectChangedIndices(
- pos, dp, trigger, perspective,
- &removed[perspective], &added[perspective]);
- }
- }
- };
-
- auto collect_for_two = [&](const DirtyPiece& dp1, const DirtyPiece& dp2) {
- for (Color perspective : { WHITE, BLACK }) {
- switch (trigger) {
- case TriggerEvent::kFriendKingMoved:
- reset[perspective] = dp1.piece[0] == make_piece(perspective, KING)
- || dp2.piece[0] == make_piece(perspective, KING);
- break;
- default:
- assert(false);
- break;
- }
- if (reset[perspective]) {
- Derived::CollectActiveIndices(
- pos, trigger, perspective, &added[perspective]);
- } else {
- Derived::CollectChangedIndices(
- pos, dp1, trigger, perspective,
- &removed[perspective], &added[perspective]);
- Derived::CollectChangedIndices(
- pos, dp2, trigger, perspective,
- &removed[perspective], &added[perspective]);
- }
- }
- };
-
- if (pos.state()->previous->accumulator.computed_accumulation) {
- const auto& prev_dp = pos.state()->dirtyPiece;
- if (prev_dp.dirty_num == 0) return;
- collect_for_one(prev_dp);
- } else {
- const auto& prev_dp = pos.state()->previous->dirtyPiece;
- if (prev_dp.dirty_num == 0) {
- const auto& prev2_dp = pos.state()->dirtyPiece;
- if (prev2_dp.dirty_num == 0) return;
- collect_for_one(prev2_dp);
- } else {
- const auto& prev2_dp = pos.state()->dirtyPiece;
- if (prev2_dp.dirty_num == 0) {
- collect_for_one(prev_dp);
- } else {
- collect_for_two(prev_dp, prev2_dp);
- }
- }
- }
- }
};
// Class template that represents the feature set
CompileTimeList<TriggerEvent, FeatureType::kRefreshTrigger>;
static constexpr auto kRefreshTriggers = SortedTriggerSet::kValues;
- private:
- // Get a list of indices for active features
- static void CollectActiveIndices(
- const Position& pos, const TriggerEvent trigger, const Color perspective,
- IndexList* const active) {
- if (FeatureType::kRefreshTrigger == trigger) {
- FeatureType::AppendActiveIndices(pos, perspective, active);
- }
- }
-
- // Get a list of indices for recently changed features
- static void CollectChangedIndices(
- const Position& pos, const DirtyPiece& dp, const TriggerEvent trigger, const Color perspective,
- IndexList* const removed, IndexList* const added) {
-
- if (FeatureType::kRefreshTrigger == trigger) {
- FeatureType::AppendChangedIndices(pos, dp, perspective, removed, added);
- }
- }
-
- // Make the base class and the class template that recursively uses itself a friend
- friend class FeatureSetBase<FeatureSet>;
- template <typename... FeatureTypes>
- friend class FeatureSet;
};
} // namespace Eval::NNUE::Features
// If vector instructions are enabled, we update and refresh the
// accumulator tile by tile such that each tile fits in the CPU's
// vector registers.
- #define TILING
+ #define VECTOR
#ifdef USE_AVX512
typedef __m512i vec_t;
static constexpr IndexType kNumRegs = 16;
#else
- #undef TILING
+ #undef VECTOR
#endif
// Number of output dimensions for one side
static constexpr IndexType kHalfDimensions = kTransformedFeatureDimensions;
- #ifdef TILING
+ #ifdef VECTOR
static constexpr IndexType kTileHeight = kNumRegs * sizeof(vec_t) / 2;
static_assert(kHalfDimensions % kTileHeight == 0, "kTileHeight must divide kHalfDimensions");
#endif
return !stream.fail();
}
- // Proceed with the difference calculation if possible
- bool UpdateAccumulatorIfPossible(const Position& pos) const {
-
- const auto now = pos.state();
- if (now->accumulator.computed_accumulation)
- return true;
-
- const auto prev = now->previous;
- if (prev) {
- if (prev->accumulator.computed_accumulation) {
- UpdateAccumulator(pos);
- return true;
- } else if (prev->previous && prev->previous->accumulator.computed_accumulation) {
- UpdateAccumulator(pos);
- return true;
- }
- }
-
- return false;
- }
-
// Convert input features
void Transform(const Position& pos, OutputType* output) const {
- if (!UpdateAccumulatorIfPossible(pos))
- RefreshAccumulator(pos);
+ UpdateAccumulator(pos, WHITE);
+ UpdateAccumulator(pos, BLACK);
const auto& accumulation = pos.state()->accumulator.accumulation;
}
private:
- // Calculate cumulative value without using difference calculation
- void RefreshAccumulator(const Position& pos) const {
-
- auto& accumulator = pos.state()->accumulator;
- IndexType i = 0;
- Features::IndexList active_indices[2];
- RawFeatures::AppendActiveIndices(pos, kRefreshTriggers[i],
- active_indices);
- for (Color perspective : { WHITE, BLACK }) {
- #ifdef TILING
- for (unsigned j = 0; j < kHalfDimensions / kTileHeight; ++j) {
- auto biasesTile = reinterpret_cast<const vec_t*>(
- &biases_[j * kTileHeight]);
- auto accTile = reinterpret_cast<vec_t*>(
- &accumulator.accumulation[perspective][i][j * kTileHeight]);
- vec_t acc[kNumRegs];
-
- for (unsigned k = 0; k < kNumRegs; ++k)
- acc[k] = biasesTile[k];
-
- for (const auto index : active_indices[perspective]) {
- const IndexType offset = kHalfDimensions * index + j * kTileHeight;
- auto column = reinterpret_cast<const vec_t*>(&weights_[offset]);
-
- for (unsigned k = 0; k < kNumRegs; ++k)
- acc[k] = vec_add_16(acc[k], column[k]);
- }
+ void UpdateAccumulator(const Position& pos, const Color c) const {
- for (unsigned k = 0; k < kNumRegs; k++)
- vec_store(&accTile[k], acc[k]);
- }
- #else
- std::memcpy(accumulator.accumulation[perspective][i], biases_,
- kHalfDimensions * sizeof(BiasType));
-
- for (const auto index : active_indices[perspective]) {
- const IndexType offset = kHalfDimensions * index;
-
- for (IndexType j = 0; j < kHalfDimensions; ++j)
- accumulator.accumulation[perspective][i][j] += weights_[offset + j];
- }
+ #ifdef VECTOR
+ // Gcc-10.2 unnecessarily spills AVX2 registers if this array
+ // is defined in the VECTOR code below, once in each branch
+ vec_t acc[kNumRegs];
#endif
- }
- #if defined(USE_MMX)
- _mm_empty();
- #endif
-
- accumulator.computed_accumulation = true;
- }
-
- // Calculate cumulative value using difference calculation
- void UpdateAccumulator(const Position& pos) const {
-
- Accumulator* prev_accumulator;
- assert(pos.state()->previous);
- if (pos.state()->previous->accumulator.computed_accumulation) {
- prev_accumulator = &pos.state()->previous->accumulator;
- }
- else {
- assert(pos.state()->previous->previous);
- assert(pos.state()->previous->previous->accumulator.computed_accumulation);
- prev_accumulator = &pos.state()->previous->previous->accumulator;
+ // Look for a usable accumulator of an earlier position. We keep track
+ // of the estimated gain in terms of features to be added/subtracted.
+ StateInfo *st = pos.state(), *next = nullptr;
+ int gain = popcount(pos.pieces()) - 2;
+ while (st->accumulator.state[c] == EMPTY)
+ {
+ auto& dp = st->dirtyPiece;
+ // The first condition tests whether an incremental update is
+ // possible at all: if this side's king has moved, it is not possible.
+ static_assert(std::is_same_v<RawFeatures::SortedTriggerSet,
+ Features::CompileTimeList<Features::TriggerEvent, Features::TriggerEvent::kFriendKingMoved>>,
+ "Current code assumes that only kFriendlyKingMoved refresh trigger is being used.");
+ if ( dp.piece[0] == make_piece(c, KING)
+ || (gain -= dp.dirty_num + 1) < 0)
+ break;
+ next = st;
+ st = st->previous;
}
- auto& accumulator = pos.state()->accumulator;
- IndexType i = 0;
- Features::IndexList removed_indices[2], added_indices[2];
- bool reset[2] = { false, false };
- RawFeatures::AppendChangedIndices(pos, kRefreshTriggers[i],
- removed_indices, added_indices, reset);
-
- #ifdef TILING
- for (IndexType j = 0; j < kHalfDimensions / kTileHeight; ++j) {
- for (Color perspective : { WHITE, BLACK }) {
+ if (st->accumulator.state[c] == COMPUTED)
+ {
+ if (next == nullptr)
+ return;
+
+ // Update incrementally in two steps. First, we update the "next"
+ // accumulator. Then, we update the current accumulator (pos.state()).
+
+ // Gather all features to be updated. This code assumes HalfKP features
+ // only and doesn't support refresh triggers.
+ static_assert(std::is_same_v<Features::FeatureSet<Features::HalfKP<Features::Side::kFriend>>,
+ RawFeatures>);
+ Features::IndexList removed[2], added[2];
+ Features::HalfKP<Features::Side::kFriend>::AppendChangedIndices(pos,
+ next->dirtyPiece, c, &removed[0], &added[0]);
+ for (StateInfo *st2 = pos.state(); st2 != next; st2 = st2->previous)
+ Features::HalfKP<Features::Side::kFriend>::AppendChangedIndices(pos,
+ st2->dirtyPiece, c, &removed[1], &added[1]);
+
+ // Mark the accumulators as computed.
+ next->accumulator.state[c] = COMPUTED;
+ pos.state()->accumulator.state[c] = COMPUTED;
+
+ // Now update the accumulators listed in info[], where the last element is a sentinel.
+ StateInfo *info[3] =
+ { next, next == pos.state() ? nullptr : pos.state(), nullptr };
+ #ifdef VECTOR
+ for (IndexType j = 0; j < kHalfDimensions / kTileHeight; ++j)
+ {
+ // Load accumulator
auto accTile = reinterpret_cast<vec_t*>(
- &accumulator.accumulation[perspective][i][j * kTileHeight]);
- vec_t acc[kNumRegs];
-
- if (reset[perspective]) {
- auto biasesTile = reinterpret_cast<const vec_t*>(
- &biases_[j * kTileHeight]);
- for (unsigned k = 0; k < kNumRegs; ++k)
- acc[k] = biasesTile[k];
- } else {
- auto prevAccTile = reinterpret_cast<const vec_t*>(
- &prev_accumulator->accumulation[perspective][i][j * kTileHeight]);
- for (IndexType k = 0; k < kNumRegs; ++k)
- acc[k] = vec_load(&prevAccTile[k]);
+ &st->accumulator.accumulation[c][0][j * kTileHeight]);
+ for (IndexType k = 0; k < kNumRegs; ++k)
+ acc[k] = vec_load(&accTile[k]);
+ for (IndexType i = 0; info[i]; ++i)
+ {
// Difference calculation for the deactivated features
- for (const auto index : removed_indices[perspective]) {
+ for (const auto index : removed[i])
+ {
const IndexType offset = kHalfDimensions * index + j * kTileHeight;
auto column = reinterpret_cast<const vec_t*>(&weights_[offset]);
-
for (IndexType k = 0; k < kNumRegs; ++k)
acc[k] = vec_sub_16(acc[k], column[k]);
}
- }
- { // Difference calculation for the activated features
- for (const auto index : added_indices[perspective]) {
+
+ // Difference calculation for the activated features
+ for (const auto index : added[i])
+ {
const IndexType offset = kHalfDimensions * index + j * kTileHeight;
auto column = reinterpret_cast<const vec_t*>(&weights_[offset]);
-
for (IndexType k = 0; k < kNumRegs; ++k)
acc[k] = vec_add_16(acc[k], column[k]);
}
- }
- for (IndexType k = 0; k < kNumRegs; ++k)
- vec_store(&accTile[k], acc[k]);
+ // Store accumulator
+ accTile = reinterpret_cast<vec_t*>(
+ &info[i]->accumulator.accumulation[c][0][j * kTileHeight]);
+ for (IndexType k = 0; k < kNumRegs; ++k)
+ vec_store(&accTile[k], acc[k]);
+ }
}
- }
- #if defined(USE_MMX)
- _mm_empty();
- #endif
#else
- for (Color perspective : { WHITE, BLACK }) {
-
- if (reset[perspective]) {
- std::memcpy(accumulator.accumulation[perspective][i], biases_,
- kHalfDimensions * sizeof(BiasType));
- } else {
- std::memcpy(accumulator.accumulation[perspective][i],
- prev_accumulator->accumulation[perspective][i],
- kHalfDimensions * sizeof(BiasType));
+ for (IndexType i = 0; info[i]; ++i)
+ {
+ std::memcpy(info[i]->accumulator.accumulation[c][0],
+ st->accumulator.accumulation[c][0],
+ kHalfDimensions * sizeof(BiasType));
+ st = info[i];
+
// Difference calculation for the deactivated features
- for (const auto index : removed_indices[perspective]) {
+ for (const auto index : removed[i])
+ {
const IndexType offset = kHalfDimensions * index;
for (IndexType j = 0; j < kHalfDimensions; ++j)
- accumulator.accumulation[perspective][i][j] -= weights_[offset + j];
+ st->accumulator.accumulation[c][0][j] -= weights_[offset + j];
}
- }
- { // Difference calculation for the activated features
- for (const auto index : added_indices[perspective]) {
+
+ // Difference calculation for the activated features
+ for (const auto index : added[i])
+ {
const IndexType offset = kHalfDimensions * index;
for (IndexType j = 0; j < kHalfDimensions; ++j)
- accumulator.accumulation[perspective][i][j] += weights_[offset + j];
+ st->accumulator.accumulation[c][0][j] += weights_[offset + j];
}
}
+ #endif
}
+ else
+ {
+ // Refresh the accumulator
+ auto& accumulator = pos.state()->accumulator;
+ accumulator.state[c] = COMPUTED;
+ Features::IndexList active;
+ Features::HalfKP<Features::Side::kFriend>::AppendActiveIndices(pos, c, &active);
+
+ #ifdef VECTOR
+ for (IndexType j = 0; j < kHalfDimensions / kTileHeight; ++j)
+ {
+ auto biasesTile = reinterpret_cast<const vec_t*>(
+ &biases_[j * kTileHeight]);
+ for (IndexType k = 0; k < kNumRegs; ++k)
+ acc[k] = biasesTile[k];
+
+ for (const auto index : active)
+ {
+ const IndexType offset = kHalfDimensions * index + j * kTileHeight;
+ auto column = reinterpret_cast<const vec_t*>(&weights_[offset]);
+
+ for (unsigned k = 0; k < kNumRegs; ++k)
+ acc[k] = vec_add_16(acc[k], column[k]);
+ }
+
+ auto accTile = reinterpret_cast<vec_t*>(
+ &accumulator.accumulation[c][0][j * kTileHeight]);
+ for (unsigned k = 0; k < kNumRegs; k++)
+ vec_store(&accTile[k], acc[k]);
+ }
+
+ #else
+ std::memcpy(accumulator.accumulation[c][0], biases_,
+ kHalfDimensions * sizeof(BiasType));
+
+ for (const auto index : active)
+ {
+ const IndexType offset = kHalfDimensions * index;
+
+ for (IndexType j = 0; j < kHalfDimensions; ++j)
+ accumulator.accumulation[c][0][j] += weights_[offset + j];
+ }
#endif
+ }
- accumulator.computed_accumulation = true;
+ #if defined(USE_MMX)
+ _mm_empty();
+ #endif
}
using BiasType = std::int16_t;
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