Comments (1)
The computation is currently done single-threaded on CPU.
Since it should be highly parallelizable, I suggest rewriting it to run on GPU.
There are various options available. Ranging from OpenCL or CUDA to TensorFlow.
Alternatively, we could try making it run on multiple CPU cores.
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Related Issues (20)
- Compilation issues under VS2017
- Easy to use, but hard to learn
- a install problem.
- Issues with taking the maximum
- Butteraugli failing due to difference in number of channels
- Evaluate butteraugli on TID-2013 and publish results HOT 2
- Please add version output
- Butteraugli Score 0.000 HOT 2
- memory leak? HOT 1
- Error while trying to build HOT 1
- butteraugli: command not found HOT 2
- Clarification needed on the input RGB format HOT 2
- new_http_archive is not defined when build
- Integrating with OSS-Fuzz
- reopen
- macOS Monterey build failed HOT 1
- Butteraugli
- Google butteraugli
- Butteraugli ππβ€οΈβ¨οΈ HOT 1
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