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Apply/bring back UseSharedPrePackedBuffers for mlas in matmul-nbit #21756

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Apply/bring back UseSharedPrePackedBuffers for mlas in matmul-nbit #21756

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26 changes: 25 additions & 1 deletion onnxruntime/contrib_ops/cpu/quantization/matmul_nbits.cc
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Original file line number Diff line number Diff line change
Expand Up @@ -222,16 +222,28 @@ Status MatMulNBits::PrePack(const Tensor& tensor, int input_idx, /*out*/ Allocat
auto qptr = tensor.DataRaw();
packed_b_ = IAllocator::MakeUniquePtr<void>(alloc, packed_b_size_, true);
MlasSQNBitGemmPackQuantBData(N_, K_, nbits_, block_size_, compute_type, qptr, packed_b_.get(), nullptr, has_zp_input_, nullptr, nullptr);
if (prepacked_weights) {
prepacked_weights->buffers_.push_back(std::move(packed_b_));
prepacked_weights->buffer_sizes_.push_back(packed_b_size_);
}
is_packed = true;
} else if (compute_type == CompInt8) {
#ifdef MLAS_TARGET_AMD64_IX86
if (input_idx == InputIndex::scales && packed_b_ != nullptr) {
auto sptr = tensor.Data<float>();
MlasSQNBitGemmPackQuantBData(N_, K_, nbits_, block_size_, compute_type, nullptr, packed_b_.get(), sptr, has_zp_input_, nullptr, nullptr);
if (prepacked_weights) {
prepacked_weights->buffers_.push_back(std::move(packed_b_));
prepacked_weights->buffer_sizes_.push_back(packed_b_size_);
}
is_packed = false;
} else if (input_idx == InputIndex::zero_points && packed_b_ != nullptr) {
auto zptr = tensor.Data<uint8_t>();
MlasSQNBitGemmPackQuantBData(N_, K_, nbits_, block_size_, compute_type, nullptr, packed_b_.get(), nullptr, has_zp_input_, zptr, nullptr);
if (prepacked_weights) {
prepacked_weights->buffers_.push_back(std::move(packed_b_));
prepacked_weights->buffer_sizes_.push_back(packed_b_size_);
}
is_packed = false;
}
#endif
Expand Down Expand Up @@ -267,7 +279,19 @@ Status MatMulNBits::UseSharedPrePackedBuffers(std::vector<BufferUniquePtr>& prep
used_shared_buffers = true;
packed_b_ = std::move(prepacked_buffers[0]);
}

#ifdef MLAS_TARGET_AMD64_IX86
const auto compute_type = static_cast<MLAS_SQNBIT_GEMM_COMPUTE_TYPE>(accuracy_level_);
if (compute_type == CompInt8) {
if (input_idx == 2) {
used_shared_buffers = true;
packed_b_ = std::move(prepacked_buffers[0]);
}
if (input_idx == 3) {
used_shared_buffers = true;
packed_b_ = std::move(prepacked_buffers[0]);
}
}
#endif // MLAS_TARGET_AMD64_IX86
#endif // defined(ORT_NEURAL_SPEED)

return Status::OK();
Expand Down
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