mirror of https://github.com/google/gemma.cpp.git
167 lines
5.4 KiB
C++
167 lines
5.4 KiB
C++
// Copyright 2024 Google LLC
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// SPDX-License-Identifier: Apache-2.0
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//
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// Licensed under the Apache License, Version 2.0 (the "License");
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// you may not use this file except in compliance with the License.
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// You may obtain a copy of the License at
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//
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// https://www.apache.org/licenses/LICENSE-2.0
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//
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// Unless required by applicable law or agreed to in writing, software
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// distributed under the License is distributed on an "AS IS" BASIS,
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// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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// See the License for the specific language governing permissions and
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// limitations under the License.
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#ifndef THIRD_PARTY_GEMMA_CPP_OPS_MATMUL_H_
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#define THIRD_PARTY_GEMMA_CPP_OPS_MATMUL_H_
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#include <stddef.h>
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// IWYU pragma: begin_exports
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#include "compression/compress.h"
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#include "util/allocator.h"
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#include "util/basics.h"
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#include "util/threading.h"
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#include "hwy/base.h"
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#include "hwy/contrib/thread_pool/thread_pool.h"
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// IWYU pragma: end_exports
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#include "hwy/per_target.h" // VectorBytes
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namespace gcpp {
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// TODO: remove deprecated typedef.
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using Range1D = IndexRange;
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// The MatMul result C[r,c] is Dot(A.Row(r), B.Col(c)). To reduce the number of
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// loads, we reuse the same A row for several B columns, which are also loaded
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// once for several rows of C. Thus we produce one 'tile' of C at a time of
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// dimensions `kRegRows` x `kRegCols`. The Reg naming is because these are
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// limited by the number of registers: 32 for NEON/SVE/AVX-512. `kRegCols` == 4
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// enables the `StoreInterleaved4` transpose in `StoreHorizontalSums`. We assume
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// and verify that `C.Cols() % kRegCols == 0`.
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constexpr size_t kRegCols = 4;
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// Choosing `kRegRows == kRegCols` minimizes the ratio of loads to FMA, because
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// we load `kRegCols + kRegRows` vectors per `kRegRows * kRegCols` element tile.
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// In general, `batch_size` (A/C rows) is not a multiple of `kRegRows`. Thus
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// functions that load or store a tile are parameterized on `kRowsPerTile`:
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// usually `kRegRows`, but `batch_size % kRegRows` on the last row (if != 0).
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constexpr size_t kRegRows = kRegCols;
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struct CacheSizes {
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CacheSizes() = default;
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CacheSizes(const BoundedTopology::Cluster& cluster) {
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// Assumes each package and cluster has the same cache sizes, and uses
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// reasonable defaults if unknown.
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l1_bytes = 32 * 1024; // typical size, rarely changes
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l2_bytes = (cluster.PrivateKiB() ? cluster.PrivateKiB() : 256) * 1024;
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l3_bytes = (cluster.SharedKiB() ? cluster.SharedKiB() : 1024) * 1024;
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}
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size_t l1_bytes;
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size_t l2_bytes;
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size_t l3_bytes;
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};
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class MMParallel {
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public:
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MMParallel() : pools_(nullptr) {}
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explicit MMParallel(NestedPools& pools) : pools_(&pools) {}
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NestedPools& Pools() const { return *pools_; }
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hwy::ThreadPool& Pool() const { return pools_->Pool(); }
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private:
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NestedPools* pools_;
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};
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// Allocations and threads, shared across MatMul calls.
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class MatMulEnv {
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public:
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explicit MatMulEnv(NestedPools& pools) : parallel(pools) {
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const size_t N = hwy::VectorBytes() / sizeof(float);
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buf_ = RowVectorBatch<float>(Extents2D(pools.MaxWorkers(), 16 * N));
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}
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RowVectorBatch<float>& Buf() { return buf_; }
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MMParallel parallel;
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// TODO: remove once no longer used.
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NestedPools& Pools() const { return parallel.Pools(); }
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hwy::ThreadPool& Pool() const { return parallel.Pool(); }
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private:
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RowVectorBatch<float> buf_;
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};
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// Used for the A and B arguments of `MatMul`, which are always const.
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// Create via MakeConstMat. This differs from `RowPtr` in that it supports the
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// `ofs` required for compressed T.
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template <typename T>
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struct ConstMat {
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ConstMat(const T* ptr, Extents2D extents, size_t ofs = 0)
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: ptr(ptr), extents(extents), ofs(ofs) {
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HWY_DASSERT(ptr != nullptr);
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}
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// TODO: support stride for page alignment.
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size_t Row(size_t r) const {
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if constexpr (HWY_IS_DEBUG_BUILD) {
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if (r >= extents.rows) {
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HWY_ABORT("ConstMat::Row %zu out of bounds %zu", r, extents.rows);
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}
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}
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return ofs + extents.cols * r;
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}
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const Extents2D& Extents() const { return extents; }
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size_t Stride() const { return extents.cols; }
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// Shrinks the row-extent of this matrix view, i.e. reduces the view to a
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// subrange of the original rows starting at row 0.
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void ShrinkRows(size_t rows) {
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HWY_ASSERT(rows <= extents.rows);
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extents.rows = rows;
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}
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const T* HWY_RESTRICT ptr;
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Extents2D extents;
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// `scale` allows expanding the smaller range of `SfpStream` to the original
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// values. MatFromWeights sets this from `MatPtr`.
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float scale = 1.0f;
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// Offset to add to `ptr`; separate because T=NuqStream does not support
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// pointer arithmetic.
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size_t ofs;
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};
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// For deducing T.
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template <typename T>
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ConstMat<T> MakeConstMat(T* HWY_RESTRICT ptr, Extents2D extents,
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size_t ofs = 0) {
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return ConstMat<T>(ptr, extents, ofs);
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}
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// For A argument to MatMul (activations).
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template <typename T>
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ConstMat<T> ConstMatFromBatch(size_t batch_size,
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const RowVectorBatch<T>& row_vectors) {
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HWY_DASSERT(batch_size <= row_vectors.BatchSize());
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return MakeConstMat(const_cast<T*>(row_vectors.Const()),
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Extents2D(batch_size, row_vectors.Cols()));
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}
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template <typename T>
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ConstMat<T> ConstMatFromWeights(const MatPtrT<T>& m, size_t ofs = 0) {
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ConstMat<T> mat = MakeConstMat(const_cast<T*>(m.data()), m.Extents(), ofs);
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mat.scale = m.scale();
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return mat;
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}
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} // namespace gcpp
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#endif // THIRD_PARTY_GEMMA_CPP_OPS_MATMUL_H_
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