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| author |  Benjamin Kramer <kramerb@google.com> | 2018-08-03 10:24:13 -0700 |
|---|---|---|
| committer |  TensorFlower Gardener <gardener@tensorflow.org> | 2018-08-03 10:28:08 -0700 |
| commit | e36c16c6720dd64ae5d8a1f8555102a1323af9ae (patch) | |
| tree | 9076cc7fa753542490bac8b1fcd2bc3a3c2ac62a /tensorflow/stream_executor/stream.h | |
| parent | 7935c176118f0e50aa657a1c68a85430b70d2245 (diff) | |
[XLA:GPU] Use strided batched gemm instead of building pointer tables.
This is mostly a huge amount of plumbing just to call into the cublas functions.
blasGemmStridedBatched has been available since CUDA 8.0.
For autotuning we'd need cublasGemmStridedBatchedEx, which is new in CUDA 9.2
so I didn't wire that up yet.
PiperOrigin-RevId: 207285707
Diffstat (limited to 'tensorflow/stream_executor/stream.h')
| -rw-r--r-- | tensorflow/stream_executor/stream.h | 32 |
1 files changed, 32 insertions, 0 deletions
diff --git a/tensorflow/stream_executor/stream.h b/tensorflow/stream_executor/stream.h index 706442a666..62d0a2062d 100644 --- a/tensorflow/stream_executor/stream.h +++ b/tensorflow/stream_executor/stream.h @@ -1557,6 +1557,38 @@ class Stream { std::complex<double> beta, const port::ArraySlice<DeviceMemory<std::complex<double>> *> &c, int ldc, int batch_count, ScratchAllocator *scratch_allocator); + Stream &ThenBlasGemmStridedBatched( + blas::Transpose transa, blas::Transpose transb, uint64 m, uint64 n, + uint64 k, float alpha, const DeviceMemory<Eigen::half> &a, int lda, + int64 stride_a, const DeviceMemory<Eigen::half> &b, int ldb, + int64 stride_b, float beta, DeviceMemory<Eigen::half> *c, int ldc, + int64 stride_c, int batch_count); + Stream &ThenBlasGemmStridedBatched( + blas::Transpose transa, blas::Transpose transb, uint64 m, uint64 n, + uint64 k, float alpha, const DeviceMemory<float> &a, int lda, + int64 stride_a, const DeviceMemory<float> &b, int ldb, int64 stride_b, + float beta, DeviceMemory<float> *c, int ldc, int64 stride_c, + int batch_count); + Stream &ThenBlasGemmStridedBatched( + blas::Transpose transa, blas::Transpose transb, uint64 m, uint64 n, + uint64 k, double alpha, const DeviceMemory<double> &a, int lda, + int64 stride_a, const DeviceMemory<double> &b, int ldb, int64 stride_b, + double beta, DeviceMemory<double> *c, int ldc, int64 stride_c, + int batch_count); + Stream &ThenBlasGemmStridedBatched( + blas::Transpose transa, blas::Transpose transb, uint64 m, uint64 n, + uint64 k, std::complex<float> alpha, + const DeviceMemory<std::complex<float>> &a, int lda, int64 stride_a, + const DeviceMemory<std::complex<float>> &b, int ldb, int64 stride_b, + std::complex<float> beta, DeviceMemory<std::complex<float>> *c, int ldc, + int64 stride_c, int batch_count); + Stream &ThenBlasGemmStridedBatched( + blas::Transpose transa, blas::Transpose transb, uint64 m, uint64 n, + uint64 k, std::complex<double> alpha, + const DeviceMemory<std::complex<double>> &a, int lda, int64 stride_a, + const DeviceMemory<std::complex<double>> &b, int ldb, int64 stride_b, + std::complex<double> beta, DeviceMemory<std::complex<double>> *c, int ldc, + int64 stride_c, int batch_count); // See BlasSupport::DoBlasHemm. Stream &ThenBlasHemm(blas::Side side, blas::UpperLower uplo, uint64 m, |