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| author | Gian Marco <gianmarco.iodice@arm.com> | 2018-02-05 15:07:36 +0000 |
|---|---|---|
| committer | Anthony Barbier <anthony.barbier@arm.com> | 2018-11-02 16:47:18 +0000 |
| commit | 1aede367b9ecab66dfaf6fb07f95720064afdea4 (patch) | |
| tree | 4ff21a0bd82bef963cd7b7a8013c0dceedb78fd5 /arm_compute/runtime/GLES_COMPUTE/functions/GCGEMM.h | |
| parent | 1167487ea8e54a76d0a3625e0aa84e2ad9ffd317 (diff) | |
| download | ComputeLibrary-1aede367b9ecab66dfaf6fb07f95720064afdea4.tar.gz | |
COMPMID-765 - Extended GEMM benchmark
Added new benchmarks GEMM in order to evaluate the performance when the
input matrix B has to be reshaped only once
Change-Id: I1c4790213704ce57ea7b28f6f362c56edccd1eb9
Reviewed-on: https://eu-gerrit-1.euhpc.arm.com/118910
Tested-by: Jenkins <bsgcomp@arm.com>
Reviewed-by: Michele DiGiorgio <michele.digiorgio@arm.com>
Reviewed-by: Anthony Barbier <anthony.barbier@arm.com>
Diffstat (limited to 'arm_compute/runtime/GLES_COMPUTE/functions/GCGEMM.h')
| -rw-r--r-- | arm_compute/runtime/GLES_COMPUTE/functions/GCGEMM.h | 18 |
1 files changed, 10 insertions, 8 deletions
diff --git a/arm_compute/runtime/GLES_COMPUTE/functions/GCGEMM.h b/arm_compute/runtime/GLES_COMPUTE/functions/GCGEMM.h index f2484cd801..8ddfae1169 100644 --- a/arm_compute/runtime/GLES_COMPUTE/functions/GCGEMM.h +++ b/arm_compute/runtime/GLES_COMPUTE/functions/GCGEMM.h @@ -1,5 +1,5 @@ /* - * Copyright (c) 2017 ARM Limited. + * Copyright (c) 2017-2018 ARM Limited. * * SPDX-License-Identifier: MIT * @@ -58,14 +58,16 @@ public: * * @note Whilst the first input tensor can be a vector, the second input tensor must be at least a matrix * - * @param[in] a First input tensor (Matrix or Vector A). Data types supported: 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] output 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 or Vector A). Data types supported: 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] output 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 IGCTensor *a, const IGCTensor *b, const IGCTensor *c, IGCTensor *output, float alpha, float beta); + void configure(const IGCTensor *a, const IGCTensor *b, const IGCTensor *c, IGCTensor *output, float alpha, float beta, const GEMMInfo &gemm_info = GEMMInfo()); // Inherited methods overridden: void run() override; |