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authorSiCong Li <sicong.li@arm.com>2019-11-05 10:43:06 +0000
committerSiCong Li <sicong.li@arm.com>2019-11-12 09:52:55 +0000
commit75041a1cb81c59a5a5ddd9b708476c0142362d9e (patch)
tree5ef625879aaa35c757ee4070f753f769f4362011 /examples/gemm_tuner/README.md
parent77d42528b796f3b8f5033785d3bbb8d9cb3fc637 (diff)
downloadComputeLibrary-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 'examples/gemm_tuner/README.md')
-rw-r--r--examples/gemm_tuner/README.md3
1 files changed, 2 insertions, 1 deletions
diff --git a/examples/gemm_tuner/README.md b/examples/gemm_tuner/README.md
index 3d5b6376e1..e8cb7e5193 100644
--- a/examples/gemm_tuner/README.md
+++ b/examples/gemm_tuner/README.md
@@ -25,4 +25,5 @@ python >= 3.6. The script will output the best configuration, along with some
analysis statistics for each strategy, and optionally save the parsed benchmark
results into csv files (one for each strategy) for further analysis.
-python GemmTuner.py -b \<benchmark_results_dir\> [-o \<out_dir\>]
+python GemmTuner.py -b \<benchmark_results_dir\> [-t \<tolerance\>]
+[-o \<out_dir\>]