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author | Andrzej Janik <[email protected]> | 2020-11-23 22:37:57 +0100 |
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committer | Andrzej Janik <[email protected]> | 2020-11-23 22:38:12 +0100 |
commit | 892e47a653a8a3f0874cda194c7c31948957c97d (patch) | |
tree | 1644228696228accf2b3cb500711fbb962e7016e | |
parent | 690f4f3ad2e1daf255749aa65ba14996ada51bbf (diff) | |
download | ZLUDA-1.tar.gz ZLUDA-1.zip |
Update README with links to GeekBench resultsv1
-rw-r--r-- | README.md | 8 |
1 files changed, 6 insertions, 2 deletions
@@ -9,9 +9,13 @@ One measurement has been done using OpenCL and another measurement has been done Performance below is normalized to OpenCL performance. 110% means that ZLUDA-implemented CUDA is 10% faster on Intel UHD 630. -![](GeekBench_5_2_3.svg) +![Performance graph](GeekBench_5_2_3.svg) -Overall in this suite of benchmarks ZLUDA is roughly 4% faster. +[ZLUDA detailed log on Geekbench.com](https://browser.geekbench.com/v5/compute/1918048) + +[OpenCL detailed log on Geekbench.com](https://browser.geekbench.com/v5/compute/1918080) + +Overall in this suite of benchmarks faster by approximately 4% on ZLUDA. ### Explanation of the results * Why is ZLUDA faster in Stereo Matching, Gaussian Blur and Depth of Field?\ |