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author | SiCong Li <sicong.li@arm.com> | 2019-11-05 10:43:06 +0000 |
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committer | SiCong Li <sicong.li@arm.com> | 2019-11-12 09:52:55 +0000 |
commit | 75041a1cb81c59a5a5ddd9b708476c0142362d9e (patch) | |
tree | 5ef625879aaa35c757ee4070f753f769f4362011 /tests/datasets/NormalizationTypesDataset.h | |
parent | 77d42528b796f3b8f5033785d3bbb8d9cb3fc637 (diff) | |
download | ComputeLibrary-75041a1cb81c59a5a5ddd9b708476c0142362d9e.tar.gz |
COMPMID-2563 Change how the best overall GEMM configuration is selected
* Based on a specified tolerance, each GEMMParam (GEMM Shape) now can
have a set of best GEMM configurations, instead of just a single one.
This improves the robustness and completeness of the tuned results, and
is in compliance with how we define the GEMMParam archetypes (the main
goal of this story)
* The tuner then tries to find the best overall GEMMConfig, from all the
best config sets, through the same voting mechanism: the config that
gets voted the most is the best overall GEMMConfig.
Change-Id: Ief770bb6ffc04629d91f1dc778eea69274e007f0
Signed-off-by: SiCong Li <sicong.li@arm.com>
Reviewed-on: https://review.mlplatform.org/c/2228
Reviewed-by: Georgios Pinitas <georgios.pinitas@arm.com>
Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>
Tested-by: Arm Jenkins <bsgcomp@arm.com>
Reviewed-by: Gian Marco Iodice <gianmarco.iodice@arm.com>
Diffstat (limited to 'tests/datasets/NormalizationTypesDataset.h')
0 files changed, 0 insertions, 0 deletions