diff options
author | Gian Marco <gianmarco.iodice@arm.com> | 2017-12-16 19:33:50 +0000 |
---|---|---|
committer | Anthony Barbier <anthony.barbier@arm.com> | 2018-11-02 16:42:33 +0000 |
commit | 1d25ed54a948639d1894c8b021940df70005d519 (patch) | |
tree | 96a29126c5b61299d64496fad7f6844412ab2cca /arm_compute/runtime/NEON/functions/NEGEMM.h | |
parent | 57b20109108a90113d29d21ce7d3c873ff19749c (diff) | |
download | ComputeLibrary-1d25ed54a948639d1894c8b021940df70005d519.tar.gz |
COMPMID-759 - CLGEMM optimization for McVail benchmarks
This patch introduces an optimization for CLGEMM on Bifrost
architectures which can bring to 40% of FMA utilization on
config 3 of McVail. The new CLGEMM does not require any reshape of
matrix A and matrix B.
This patch also adds the auto-config in CLConvolutionLayer and CLGEMM
and extends the interface for NEGEMM and CLGEMM.
Change-Id: Ibb354eda45e9ca64b14a99700fb21dff5989dda9
Reviewed-on: https://eu-gerrit-1.euhpc.arm.com/113716
Tested-by: Jenkins <bsgcomp@arm.com>
Reviewed-by: Michalis Spyrou <michalis.spyrou@arm.com>
Reviewed-by: Anthony Barbier <anthony.barbier@arm.com>
Diffstat (limited to 'arm_compute/runtime/NEON/functions/NEGEMM.h')
-rw-r--r-- | arm_compute/runtime/NEON/functions/NEGEMM.h | 18 |
1 files changed, 11 insertions, 7 deletions
diff --git a/arm_compute/runtime/NEON/functions/NEGEMM.h b/arm_compute/runtime/NEON/functions/NEGEMM.h index 068e7c5ce8..4b0614badc 100644 --- a/arm_compute/runtime/NEON/functions/NEGEMM.h +++ b/arm_compute/runtime/NEON/functions/NEGEMM.h @@ -58,14 +58,16 @@ public: * @note GEMM: General Matrix Multiply - [alpha * A * B + beta * C]. * @note GEMM: The tensors a, b, c, d must have the same data type. You should not mix data types when calling this function. * - * @param[in] a First input tensor (Matrix A or Vector A). Data type supported: QS8/QS16/F16/F32 - * @param[in] b Second input tensor (Matrix B). Data type supported: same as @p a - * @param[in] c Third input tensor (Matrix C). It can be a nullptr if just the multiplication between @p a and @p b is needed. Data type supported: same as @p a - * @param[out] d Output tensor. Data type supported: same as @p a - * @param[in] alpha Weight of the matrix product - * @param[in] beta Weight of matrix C + * @param[in] a First input tensor (Matrix A or Vector A). Data type supported: QS8/QS16/F16/F32 + * @param[in] b Second input tensor (Matrix B). Data type supported: same as @p a + * @param[in] c Third input tensor (Matrix C). It can be a nullptr if just the multiplication between @p a and @p b is needed. Data type supported: same as @p a + * @param[out] d Output tensor. Data type supported: same as @p a + * @param[in] alpha Weight of the matrix product + * @param[in] beta Weight of matrix C + * @param[in] gemm_info (Optional) Specifies if the matrix A and/or matrix B have been reshaped and + * if the reshape of matrix B should happen only for the first run */ - void configure(const ITensor *a, const ITensor *b, const ITensor *c, ITensor *d, float alpha, float beta); + void configure(const ITensor *a, const ITensor *b, const ITensor *c, ITensor *d, float alpha, float beta, const GEMMInfo &gemm_info = GEMMInfo()); // Inherited methods overridden: void run() override; @@ -82,6 +84,8 @@ private: Tensor _workspace; bool _run_vector_matrix_multiplication; bool _run_addition; + bool _is_first_run; + bool _reshape_b_only_on_first_run; }; } #endif /*__ARM_COMPUTE_NEGEMM_H__ */ |