diff options
| author | Jianyu Huang <jianyuhuang@fb.com> | 2019-08-06 19:35:42 +0300 |
|---|---|---|
| committer | Facebook Github Bot <facebook-github-bot@users.noreply.github.com> | 2019-08-06 19:50:51 +0300 |
| commit | d8b3323668fdd15dc70e9cb43ab16e96f4846eeb (patch) | |
| tree | d48a6818c14575d92e68bf1ffb621d646a6c893e /src/ExecuteKernelU8S8.cc | |
| parent | 0d5d057ca941ebb511bdc6178fc26c23e6c4a953 (diff) | |
Integrate VNNI into FBGEMM master branch (#113)
Summary:
Pull Request resolved: https://github.com/pytorch/FBGEMM/pull/113
Adding the VNNI support in FBGEMM.
Reviewed By: dskhudia
Differential Revision: D16276574
fbshipit-source-id: 832ccdb27339489ebc138f3b2678e53d107c1b79
Diffstat (limited to 'src/ExecuteKernelU8S8.cc')
| -rw-r--r-- | src/ExecuteKernelU8S8.cc | 47 |
1 files changed, 41 insertions, 6 deletions
diff --git a/src/ExecuteKernelU8S8.cc b/src/ExecuteKernelU8S8.cc index f7292fd..0a4ff55 100644 --- a/src/ExecuteKernelU8S8.cc +++ b/src/ExecuteKernelU8S8.cc @@ -49,7 +49,8 @@ ExecuteKernel< throw std::runtime_error("Failed to initialize cpuinfo!"); } if (params) { - if (fbgemmHasAvx512Support() || fbgemmHasAvx2Support()) { + if (fbgemmHasAvx512VnniSupport() || fbgemmHasAvx512Support() || + fbgemmHasAvx2Support()) { mbSize_ = params->MCB; nbSize_ = params->NCB; nrMinSize_ = params->NR_MIN; @@ -59,7 +60,20 @@ ExecuteKernel< assert(0 && "unsupported architecure"); } } else { - if (fbgemmHasAvx512Support()) { + if (fbgemmHasAvx512VnniSupport()) { + mbSize_ = PackingTraits< + int8_t, + typename packingAMatrix::accType, + inst_set_t::avx512_vnni>::MCB; + nbSize_ = PackingTraits< + int8_t, + typename packingAMatrix::accType, + inst_set_t::avx512_vnni>::NCB; + nrMinSize_ = PackingTraits< + int8_t, + typename packingAMatrix::accType, + inst_set_t::avx512_vnni>::NR_MIN; + } else if (fbgemmHasAvx512Support()) { mbSize_ = PackingTraits< int8_t, typename packingAMatrix::accType, @@ -118,7 +132,25 @@ void ExecuteKernel< typename BaseType::jit_micro_kernel_fp fn; - if (fbgemmHasAvx512Support()) { + if (fbgemmHasAvx512VnniSupport()) { + if (std::is_same<typename packingAMatrix::accType, std::int16_t>::value) { + // For AVX512VNNI, we redirect int16_t to int32_t accumulation. + CodeGenBase<uint8_t, int8_t, int32_t, int32_t> codeObj; + fn = codeObj.getOrCreate<inst_set_t::avx512_vnni>( + accum, + packed_rows_A, + packedB_.blockColSize(), + packedA_.numPackedCols(), + nbSize_); + } else { + fn = BaseType::template getOrCreate<inst_set_t::avx512_vnni>( + accum, + packed_rows_A, + packedB_.blockColSize(), + packedA_.numPackedCols(), + nbSize_); + } + } else if (fbgemmHasAvx512Support()) { fn = BaseType::template getOrCreate<inst_set_t::avx512>( accum, packed_rows_A, @@ -148,7 +180,10 @@ void ExecuteKernel< if (jb == bColBlocks - 1) { int nc = ((packedB_.lastBcol() - 1) / nrMinSize_ + 1) * nrMinSize_; if (nc != nbSize_) { - if (fbgemmHasAvx512Support()) { + if (fbgemmHasAvx512VnniSupport()) { + fn = BaseType::template getOrCreate<inst_set_t::avx512_vnni>( + accum, packed_rows_A, nc, packedA_.numPackedCols(), nbSize_); + } else if (fbgemmHasAvx512Support()) { fn = BaseType::template getOrCreate<inst_set_t::avx512>( accum, packed_rows_A, nc, packedA_.numPackedCols(), nbSize_); } else if (fbgemmHasAvx2Support()) { @@ -213,7 +248,7 @@ void ExecuteKernel< int32_t nSize = C_buffer_start == C_tile_ ? jb * nbSize_ : packedB_.numCols(); if (nSize) { - if (fbgemmHasAvx512Support()) { + if (fbgemmHasAvx512VnniSupport() || fbgemmHasAvx512Support()) { // TODO: avx512 path // Currently use avx2 code outputProcess_.template f<inst_set_t::avx2>( @@ -238,7 +273,7 @@ void ExecuteKernel< if (C_buffer_start == C_tile_) { // When C_tile_ scratchpad was used to avoid accessing memory past // C_buffer_ . - if (fbgemmHasAvx512Support()) { + if (fbgemmHasAvx512VnniSupport() || fbgemmHasAvx512Support()) { // TODO: avx512 path // Currently use avx2 code outputProcess_.template f<inst_set_t::avx2>( |