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About CUDA version and TRT version of 1.14.0 #870

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hope366 opened this issue Dec 28, 2023 · 4 comments
Open

About CUDA version and TRT version of 1.14.0 #870

hope366 opened this issue Dec 28, 2023 · 4 comments

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@hope366
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hope366 commented Dec 28, 2023

Thank you for your efforts in the development of katago.
Also, thank you for letting me use Katago for free.

The cuda version of 1.14.0 worked with the following three libraries that I had been using since before 1.13.0.

  • cudnn_cnn_infer64_8.dll
  • cudnn_ops_infer64_8.dll
  • cudnn64_8.dll
    The release page says "CUDA 12.1.x and CUDNN 8.9.7 are required", but if it works, does it matter which one I use?

Until now, when I used the cuda version, in addition to the three above, I also placed the following three in the same folder.
If the above three work, are the bottom three unnecessary?

  • cublas64_11.dll
  • cublasLt64_11.dll
  • cudart64_110.dll

1.14.0-trt did not work with dependent TensorRT-8.5.2.2. I prepared a new TensorRT-8.6.1.6 and it worked.
Compared to 1.13.1-trt, 1.14.0-trt is about 10% faster.

@lightvector
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Thanks for testing!

If it works with an older CUDA you can still use the older CUDA, but I've switched my testing to be on CUDA 12 going forward, so officially that's the only one that will be recommended.

Also, when I upgraded my own machines from CUDA 11.4 to CUDA 12.1, I also got like a 10% improvement on the CUDA backend too, so there may be some benefits to upgrading as well even if an older version works.

@hope366
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hope366 commented Dec 29, 2023

Also, when I upgraded my own machines from CUDA 11.4 to CUDA 12.1, I also got like a 10% improvement on the CUDA backend too, so there may be some benefits to upgrading as well even if an older version works.

Well, that's good news. I would like to upgrade to CUDA12.1 and observe how the speed changes.

@hope366
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hope366 commented Dec 29, 2023

I have prepared CUDA and CUDNN as recommended on the release page.

  • CUDA 12.1.1
  • cudnn-8.9.7.29_cuda12

The following files were placed in the katago-cuda folder.

無題

I ran a benchmark test to compare it to my previous environment, and the speed improvement was only around 3%.
The CUDA and CUDNN that I have been using so far were borrowed from Megapack, but they may not be that old.
That may be why I didn't see a significant speed improvement.

Are the six files shown in the image above necessary and sufficient to run the newly released katago-cuda?

@hope366
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hope366 commented Dec 29, 2023

I said that the speedup rate is 3%, but it changes depending on the number of threads used, and it ranges from -1 to +11%.
In most cases, the increase was between 3% and 5%.

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