mirror of https://github.com/google/gemma.cpp.git
Even-odd layout MatVecs for bf16 weights.
This commit is contained in:
parent
7a12e29027
commit
0816a1070d
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@ -51,6 +51,20 @@ namespace gcpp {
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namespace HWY_NAMESPACE {
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namespace hn = hwy::HWY_NAMESPACE;
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template <class DF, HWY_IF_F32_D(DF)>
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HWY_INLINE void Bf16ToF32EO(const DF df32,
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const hwy::bfloat16_t* HWY_RESTRICT in,
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hn::Vec<DF>& v_even,
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hn::Vec<DF>& v_odd) {
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const hn::Repartition<hwy::bfloat16_t, DF> dbf16;
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const hn::RebindToUnsigned<decltype(df32)> du32;
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const auto odd = Set(du32, 0xFFFF0000u);
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const auto interleaved = BitCast(du32, LoadU(dbf16, in));
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v_even = BitCast(df32, hn::ShiftLeft<16>(interleaved));
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v_odd = BitCast(df32, And(interleaved, odd));
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}
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// Enables generic code independent of compression type.
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template <typename T> // primary, must specialize
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struct CompressTraits {};
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@ -58,6 +72,7 @@ struct CompressTraits {};
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template <>
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struct CompressTraits<float> {
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using MatT = float;
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static constexpr bool supports_eo = false;
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template <class DF, HWY_IF_F32_D(DF)>
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static HWY_INLINE void Compress(DF df, const float* HWY_RESTRICT in,
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@ -111,6 +126,7 @@ struct CompressTraits<float> {
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template <>
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struct CompressTraits<hwy::bfloat16_t> {
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using MatT = hwy::bfloat16_t;
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static constexpr bool supports_eo = true;
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template <class DF, HWY_IF_F32_D(DF)>
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static HWY_INLINE void Compress(DF df, const float* HWY_RESTRICT in,
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@ -219,11 +235,60 @@ struct CompressTraits<hwy::bfloat16_t> {
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// bf16*bf16.
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return hn::Dot::Compute<kAssumptions>(d_vec, vec_aligned, in + in_ofs, num);
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}
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// Computes the dot product of an even-odd deinterleaved, f32 `vec_aligned`
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// and a column- major matrix `in`. `vec_aligned` should be aligned and
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// alternate even-indexed `hn::Lanes(df32)` elements followed by odd-indexed
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// `hn::Lanes(df32)` elements.
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template <class DF, HWY_IF_F32_D(DF)>
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static HWY_INLINE float DotEO(
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const DF df32, const hwy::bfloat16_t* HWY_RESTRICT in, size_t in_ofs,
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const float* HWY_RESTRICT vec_aligned, size_t num) {
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HWY_DASSERT(num >= (hn::Lanes(df32) * 2) && (num % (hn::Lanes(df32) * 2)) == 0);
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HWY_DASSERT((in_ofs % (hn::Lanes(df32) * 2)) == 0);
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HWY_DASSERT(hn::IsAligned(df32, vec_aligned));
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const hn::Repartition<hwy::bfloat16_t, DF> dbf16;
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using VF32 = decltype(Zero(df32));
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const size_t N = Lanes(dbf16);
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VF32 sum0 = Zero(df32);
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VF32 sum1 = Zero(df32);
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VF32 sum2 = Zero(df32);
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VF32 sum3 = Zero(df32);
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const hn::RebindToUnsigned<decltype(df32)> du32;
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using VU32 = hn::VFromD<decltype(du32)>;
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const VU32 odd = Set(du32, 0xFFFF0000u);
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VF32 be0, bo0, be1, bo1;
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for (size_t i = 0; i < num; /* i += 2 * N */) {
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const VF32 ae0 = Load(df32, vec_aligned + i);
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const VF32 ao0 = Load(df32, vec_aligned + i + (N / 2));
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Bf16ToF32EO(df32, in + in_ofs + i, be0, bo0);
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i += N;
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sum0 = hn::MulAdd(ae0, be0, sum0);
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sum1 = hn::MulAdd(ao0, bo0, sum1);
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const VF32 ae1 = Load(df32, vec_aligned + i);
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const VF32 ao1 = Load(df32, vec_aligned + i + (N / 2));
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Bf16ToF32EO(df32, in + in_ofs + i, be1, bo1);
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i += N;
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sum2 = hn::MulAdd(ae1, be1, sum2);
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sum3 = hn::MulAdd(ao1, bo1, sum3);
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}
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sum0 = Add(sum0, sum1);
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sum2 = Add(sum2, sum3);
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sum0 = Add(sum0, sum2);
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return ReduceSum(df32, sum0);
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}
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};
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template <>
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struct CompressTraits<SfpStream> {
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using MatT = SfpStream;
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static constexpr bool supports_eo = false;
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template <class DF, HWY_IF_F32_D(DF)>
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static HWY_INLINE void Compress(DF df, const float* in, size_t num,
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@ -273,6 +338,7 @@ struct CompressTraits<SfpStream> {
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template <>
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struct CompressTraits<NuqStream> {
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using MatT = NuqStream;
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static constexpr bool supports_eo = false;
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template <class DF, HWY_IF_F32_D(DF)>
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static HWY_INLINE void Compress(DF df, const float* in, size_t num,
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@ -425,16 +491,22 @@ HWY_INLINE float Dot(DF df, const ArrayT& compressed, size_t compressed_ofs,
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}
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// Returns dot product with `vec_aligned` of length `num`.
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template <class DF, typename MatT, size_t kCapacity, typename VecT>
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template <bool kVecEO, class DF, typename MatT, size_t kCapacity, typename VecT>
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HWY_INLINE float Dot(DF df, const CompressedArray<MatT, kCapacity>& compressed,
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size_t compressed_ofs, const VecT* vec_aligned,
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size_t num) {
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HWY_DASSERT(compressed_ofs + num <= compressed.size());
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HWY_DASSERT(hn::IsAligned(df, vec_aligned));
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using Traits = CompressTraits<MatT>;
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return (compressed.scale() * Traits::Dot(df, compressed.size(),
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compressed.data(), compressed_ofs,
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vec_aligned, num));
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float dot_result;
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if constexpr (kVecEO) {
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dot_result = Traits::DotEO(df, compressed.data(), compressed_ofs,
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vec_aligned, num);
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} else {
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dot_result = Traits::Dot(df, compressed.size(), compressed.data(),
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compressed_ofs, vec_aligned, num);
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}
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return compressed.scale() * dot_result;
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}
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// Callback used by ForeachTensor.
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210
gemma/ops.h
210
gemma/ops.h
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@ -92,6 +92,43 @@ HWY_INLINE constexpr size_t RowsPerStrip() {
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return kRowsPerStrip;
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}
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HWY_INLINE void ToEvenOddF32(
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const hwy::bfloat16_t* HWY_RESTRICT vec_aligned, const size_t size,
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float* HWY_RESTRICT out) {
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const hn::ScalableTag<float> df;
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const hn::Repartition<hwy::bfloat16_t, decltype(df)> dbf16;
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const hn::RebindToUnsigned<decltype(df)> du32;
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const auto odd = Set(du32, 0xFFFF0000u);
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using VF32 = decltype(hn::Zero(df));
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HWY_DASSERT(size % hn::Lanes(dbf16) == 0);
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HWY_DASSERT(hn::IsAligned(df, vec_aligned));
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VF32 veven, vodd;
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for (size_t i = 0; i < size; i += hn::Lanes(dbf16)) {
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Bf16ToF32EO(df, vec_aligned + i, veven, vodd);
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hn::Store(veven, df, out + i);
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hn::Store(vodd, df, out + i + hn::Lanes(df));
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}
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}
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HWY_INLINE void ToEvenOddF32(
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const float* HWY_RESTRICT vec_aligned, const size_t size,
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float* HWY_RESTRICT out) {
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const hn::ScalableTag<float> df;
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using VF = hn::Vec<decltype(df)>;
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HWY_DASSERT(size % (hn::Lanes(df) * 2) == 0);
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HWY_DASSERT(hn::IsAligned(df, vec_aligned));
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VF vec0, vec1;
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for (size_t i = 0; i < size; i += hn::Lanes(df) * 2) {
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hn::LoadInterleaved2(df, vec_aligned + i, vec0, vec1);
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hn::Store(vec0, df, out + i);
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hn::Store(vec1, df, out + i + hn::Lanes(df));
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}
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}
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// Simple version without tiling nor threading.
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template <bool kAdd, size_t kOuter, size_t kInner, typename ArrayT,
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typename VecT, typename AddT>
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@ -113,12 +150,38 @@ HWY_INLINE void MatVecAddLoop(const ArrayT& mat, const size_t mat_ofs,
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}
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}
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template <bool kAdd, size_t kOuter, size_t kInner, typename VecT, typename AddT,
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size_t kCapacity>
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HWY_INLINE void MatVecAddLoop(
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const CompressedArray<hwy::bfloat16_t, kCapacity>& mat,
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const size_t mat_ofs,
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const VecT* HWY_RESTRICT vec_aligned,
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const AddT* HWY_RESTRICT add,
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float* HWY_RESTRICT out) {
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PROFILER_ZONE("MatVecAddLoop");
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const hn::ScalableTag<float> df;
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const auto vec_dequant = hwy::AllocateAligned<float>(kInner);
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ToEvenOddF32(vec_aligned, kInner, vec_dequant.get());
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for (size_t idx_row = 0; idx_row < kOuter; ++idx_row) {
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const size_t row_ofs = mat_ofs + idx_row * kInner;
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if constexpr (kAdd) {
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out[idx_row] = hwy::ConvertScalarTo<float>(add[idx_row]) +
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Dot<true>(df, mat, row_ofs, vec_dequant.get(), kInner);
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} else {
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out[idx_row] = Dot<true>(df, mat, row_ofs, vec_dequant.get(), kInner);
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}
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}
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}
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template <size_t kOuter, size_t kInner, typename ArrayT, typename VecT>
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HWY_INLINE void MatVecLoop(const ArrayT& mat, const size_t mat_ofs,
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const VecT* HWY_RESTRICT vec_aligned,
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float* HWY_RESTRICT out) {
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MatVecAddLoop<false, kOuter, kInner, ArrayT, VecT, VecT>(
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mat, mat_ofs, vec_aligned, /*add=*/nullptr, out);
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MatVecAddLoop<false, kOuter, kInner>(
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mat, mat_ofs, vec_aligned, /*add=*/(VecT*)nullptr, out);
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}
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// Simple version without tiling nor threading, but two offsets/outputs.
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@ -166,20 +229,21 @@ namespace detail {
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// For each i = [0, num_rows), compute partial (length `num_cols`) dot product
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// of row i with `vec_aligned` and add into `out[i]`. The upper-left coordinate
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// of the tile is r0, c0.
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template <class DF, typename ArrayT, typename VecT>
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template <bool kVecEO, class DF, typename ArrayT, typename VecT>
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HWY_INLINE void AccumulatePartialDotProducts(
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DF df, const ArrayT& mat, size_t mat_ofs, size_t mat_stride, size_t r0,
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size_t c0, size_t num_rows, size_t num_cols,
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const VecT* HWY_RESTRICT vec_aligned, float* HWY_RESTRICT out) {
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for (size_t idx_row = 0; idx_row < num_rows; ++idx_row) {
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const size_t row_ofs = mat_ofs + (r0 + idx_row) * mat_stride;
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out[idx_row] += Dot(df, mat, row_ofs + c0, vec_aligned + c0, num_cols);
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out[idx_row] += Dot<kVecEO>(df, mat, row_ofs + c0, vec_aligned + c0, num_cols);
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}
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}
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// Same as above, but sets out[i] to the first partial dot product +
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// init (if kInit), which avoids having to zero-initialize and accumulate.
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template <bool kInit, class DF, typename ArrayT, typename VecT, typename InitT>
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// Same as AccumulatePartialDotProducts, but sets out[i] to the first partial
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// dot product + init (if kInit), which avoids having to zero-initialize and
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// accumulate.
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template <bool kVecEO, bool kInit, class DF, typename ArrayT, typename VecT, typename InitT>
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HWY_INLINE void SetFirstPartialDotProducts(DF df, const ArrayT& mat,
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size_t mat_ofs, size_t mat_stride,
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size_t r0, size_t c0,
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@ -191,9 +255,9 @@ HWY_INLINE void SetFirstPartialDotProducts(DF df, const ArrayT& mat,
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const size_t row_ofs = mat_ofs + (r0 + idx_row) * mat_stride;
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if constexpr (kInit) {
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out[idx_row] = hwy::ConvertScalarTo<float>(init[idx_row + r0]) +
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Dot(df, mat, row_ofs + c0, vec_aligned + c0, num_cols);
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Dot<kVecEO>(df, mat, row_ofs + c0, vec_aligned + c0, num_cols);
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} else {
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out[idx_row] = Dot(df, mat, row_ofs + c0, vec_aligned + c0, num_cols);
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out[idx_row] = Dot<kVecEO>(df, mat, row_ofs + c0, vec_aligned + c0, num_cols);
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}
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}
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}
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@ -202,7 +266,8 @@ HWY_INLINE void SetFirstPartialDotProducts(DF df, const ArrayT& mat,
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// horizontal strip of the entire matrix); the result is the full dot product
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// for rows r in [r0, r0 + num_rows) + optionally the add vector, which we store
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// into in out[r - r0].
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template <bool kAdd, class DF, typename ArrayT, typename VecT, typename AddT>
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template <bool kVecEO, bool kAdd, class DF, typename ArrayT, typename VecT,
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typename AddT>
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HWY_INLINE void FullDotProductsForStrip(DF df, const ArrayT& mat,
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size_t mat_ofs, size_t mat_stride,
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size_t r0, size_t num_rows,
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@ -211,25 +276,27 @@ HWY_INLINE void FullDotProductsForStrip(DF df, const ArrayT& mat,
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float* HWY_RESTRICT out) {
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// Tall and skinny: set `out` to the single dot product.
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if (mat_stride < MaxCols()) {
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SetFirstPartialDotProducts<kAdd>(df, mat, mat_ofs, mat_stride, r0, 0,
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num_rows, mat_stride, vec_aligned, add,
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out);
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SetFirstPartialDotProducts<kVecEO, kAdd>(df, mat, mat_ofs, mat_stride, r0,
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0, num_rows, mat_stride,
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vec_aligned, add, out);
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return;
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}
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// We have at least MaxCols, so start by setting `out` to that:
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SetFirstPartialDotProducts<kAdd>(df, mat, mat_ofs, mat_stride, r0, 0,
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num_rows, MaxCols(), vec_aligned, add, out);
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SetFirstPartialDotProducts<kVecEO, kAdd>(df, mat, mat_ofs, mat_stride, r0, 0,
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num_rows, MaxCols(), vec_aligned,
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add, out);
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// For further multiples of MaxCols, accumulate. Remainders handled below.
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size_t c0 = MaxCols();
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for (; c0 <= mat_stride - MaxCols(); c0 += MaxCols()) {
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AccumulatePartialDotProducts(df, mat, mat_ofs, mat_stride, r0, c0, num_rows,
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MaxCols(), vec_aligned, out);
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AccumulatePartialDotProducts<kVecEO>(df, mat, mat_ofs, mat_stride, r0, c0,
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num_rows, MaxCols(), vec_aligned, out);
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}
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if (c0 < mat_stride) { // Final cols
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AccumulatePartialDotProducts(df, mat, mat_ofs, mat_stride, r0, c0, num_rows,
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mat_stride - c0, vec_aligned, out);
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AccumulatePartialDotProducts<kVecEO>(df, mat, mat_ofs, mat_stride, r0, c0,
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num_rows, mat_stride - c0, vec_aligned,
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out);
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}
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}
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@ -254,9 +321,9 @@ HWY_INLINE void MatVecAdd(const ArrayT& mat, const size_t mat_ofs,
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pool.Run(0, kNumStrips, [&](const uint64_t strip, size_t thread) HWY_ATTR {
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PROFILER_ZONE("MatVec.lambda");
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const size_t r0 = strip * kRowsPerStrip;
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detail::FullDotProductsForStrip<kAdd>(df, mat, mat_ofs, kInner, r0,
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kRowsPerStrip, vec_aligned, add,
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out + r0);
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detail::FullDotProductsForStrip<false, kAdd>(df, mat, mat_ofs, kInner, r0,
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kRowsPerStrip, vec_aligned,
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add, out + r0);
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});
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// Remaining rows
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@ -264,8 +331,83 @@ HWY_INLINE void MatVecAdd(const ArrayT& mat, const size_t mat_ofs,
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if (r0 < kOuter) {
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PROFILER_ZONE("MatVec remainder");
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const size_t num_rows = kOuter - r0;
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detail::FullDotProductsForStrip<kAdd>(df, mat, mat_ofs, kInner, r0,
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num_rows, vec_aligned, add, out + r0);
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detail::FullDotProductsForStrip<false, kAdd>(df, mat, mat_ofs, kInner, r0,
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num_rows, vec_aligned, add,
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out + r0);
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}
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}
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// A specialization of MatVecAdd to float32 vectors which first rearranges the
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// vector to even-odd layout.
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template <bool kAdd, size_t kOuter, size_t kInner, typename ArrayT,
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typename AddT,
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std::enable_if_t<CompressTraits<typename ArrayT::value_type>::supports_eo, bool> = true>
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HWY_INLINE void MatVecAdd(const ArrayT& mat, const size_t mat_ofs,
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const float* HWY_RESTRICT const vec_aligned,
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const AddT* HWY_RESTRICT const add,
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float* HWY_RESTRICT out, hwy::ThreadPool& pool) {
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PROFILER_ZONE("MatVecAdd");
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const hn::ScalableTag<float> df;
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constexpr size_t kRowsPerStrip = RowsPerStrip<kOuter>();
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constexpr size_t kNumStrips = kOuter / kRowsPerStrip;
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const auto vec_dequant = hwy::AllocateAligned<float>(kInner);
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ToEvenOddF32(vec_aligned, kInner, vec_dequant.get());
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// For each entire strip.
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pool.Run(0, kNumStrips, [&](const uint64_t strip, size_t thread) HWY_ATTR {
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PROFILER_ZONE("MatVec.lambda");
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const size_t r0 = strip * kRowsPerStrip;
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detail::FullDotProductsForStrip<true, kAdd>(
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df, mat, mat_ofs, kInner, r0, kRowsPerStrip, vec_dequant.get(), add,
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out + r0);
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});
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// Remaining rows
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const size_t r0 = kNumStrips * kRowsPerStrip;
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if (r0 < kOuter) {
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PROFILER_ZONE("MatVec remainder");
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const size_t num_rows = kOuter - r0;
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||||
detail::FullDotProductsForStrip<true, kAdd>(
|
||||
df, mat, mat_ofs, kInner, r0, num_rows, vec_dequant.get(), add, out + r0);
|
||||
}
|
||||
}
|
||||
|
||||
// A specialization of MatVecAdd to bf16 vectors which first rearranges the
|
||||
// vector to even-odd layout.
|
||||
template <bool kAdd, size_t kOuter, size_t kInner, typename ArrayT,
|
||||
typename AddT,
|
||||
std::enable_if_t<CompressTraits<typename ArrayT::value_type>::supports_eo, bool> = true>
|
||||
HWY_INLINE void MatVecAdd(const ArrayT& mat, const size_t mat_ofs,
|
||||
const hwy::bfloat16_t* HWY_RESTRICT const vec_aligned,
|
||||
const AddT* HWY_RESTRICT const add,
|
||||
float* HWY_RESTRICT out, hwy::ThreadPool& pool) {
|
||||
PROFILER_ZONE("MatVecAdd");
|
||||
|
||||
const hn::ScalableTag<float> df;
|
||||
constexpr size_t kRowsPerStrip = RowsPerStrip<kOuter>();
|
||||
constexpr size_t kNumStrips = kOuter / kRowsPerStrip;
|
||||
|
||||
const auto vec_dequant = hwy::AllocateAligned<float>(kInner);
|
||||
ToEvenOddF32(vec_aligned, kInner, vec_dequant.get());
|
||||
|
||||
// For each entire strip.
|
||||
pool.Run(0, kNumStrips, [&](const uint64_t strip, size_t thread) HWY_ATTR {
|
||||
PROFILER_ZONE("MatVec.lambda");
|
||||
const size_t r0 = strip * kRowsPerStrip;
|
||||
detail::FullDotProductsForStrip<true, kAdd>(
|
||||
df, mat, mat_ofs, kInner, r0, kRowsPerStrip, vec_dequant.get(), add,
|
||||
out + r0);
|
||||
});
|
||||
|
||||
// Remaining rows
|
||||
const size_t r0 = kNumStrips * kRowsPerStrip;
|
||||
if (r0 < kOuter) {
|
||||
PROFILER_ZONE("MatVec remainder");
|
||||
const size_t num_rows = kOuter - r0;
|
||||
detail::FullDotProductsForStrip<true, kAdd>(
|
||||
df, mat, mat_ofs, kInner, r0, num_rows, vec_dequant.get(), add, out + r0);
|
||||
}
|
||||
}
|
||||
|
||||
|
|
@ -273,8 +415,8 @@ template <size_t kOuter, size_t kInner, typename ArrayT, typename VecT>
|
|||
HWY_INLINE void MatVec(const ArrayT& mat, const size_t mat_ofs,
|
||||
const VecT* HWY_RESTRICT const vec_aligned,
|
||||
float* HWY_RESTRICT out, hwy::ThreadPool& pool) {
|
||||
MatVecAdd<false, kOuter, kInner, ArrayT, VecT, VecT>(
|
||||
mat, mat_ofs, vec_aligned, /*add=*/nullptr, out, pool);
|
||||
MatVecAdd<false, kOuter, kInner>(
|
||||
mat, mat_ofs, vec_aligned, /*add=*/(VecT *)nullptr, out, pool);
|
||||
}
|
||||
|
||||
template <class D, HWY_IF_F32_D(D)>
|
||||
|
|
@ -401,12 +543,12 @@ HWY_NOINLINE void TwoMatVecAdd(
|
|||
pool.Run(0, kNumStrips, [&](const uint64_t strip, size_t thread) HWY_ATTR {
|
||||
PROFILER_ZONE("TwoMatVec.lambda");
|
||||
const size_t r0 = strip * kRowsPerStrip;
|
||||
detail::FullDotProductsForStrip<kAdd>(df, mat0, mat_ofs, kInner, r0,
|
||||
kRowsPerStrip, vec_aligned, add0,
|
||||
out0 + r0);
|
||||
detail::FullDotProductsForStrip<kAdd>(df, mat1, mat_ofs, kInner, r0,
|
||||
kRowsPerStrip, vec_aligned, add1,
|
||||
out1 + r0);
|
||||
detail::FullDotProductsForStrip<false, kAdd>(
|
||||
df, mat0, mat_ofs, kInner, r0, kRowsPerStrip, vec_aligned, add0,
|
||||
out0 + r0);
|
||||
detail::FullDotProductsForStrip<false, kAdd>(
|
||||
df, mat1, mat_ofs, kInner, r0, kRowsPerStrip, vec_aligned, add1,
|
||||
out1 + r0);
|
||||
});
|
||||
|
||||
// Remaining rows
|
||||
|
|
@ -414,9 +556,9 @@ HWY_NOINLINE void TwoMatVecAdd(
|
|||
if (r0 < kOuter) {
|
||||
PROFILER_ZONE("TwoMatVec remainder");
|
||||
const size_t num_rows = kOuter - r0;
|
||||
detail::FullDotProductsForStrip<kAdd>(
|
||||
detail::FullDotProductsForStrip<false, kAdd>(
|
||||
df, mat0, mat_ofs, kInner, r0, num_rows, vec_aligned, add0, out0 + r0);
|
||||
detail::FullDotProductsForStrip<kAdd>(
|
||||
detail::FullDotProductsForStrip<false, kAdd>(
|
||||
df, mat1, mat_ofs, kInner, r0, num_rows, vec_aligned, add1, out1 + r0);
|
||||
}
|
||||
}
|
||||
|
|
|
|||
Loading…
Reference in New Issue