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Does using kilosort3 in docker require GPU access now? #3562
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Hi, Kilosort3 has always required a GPU. The docker image comes with per-installed CUDA binaries, but the GPU needs to be available on the system. Does running |
yeah running nvidia-smi works and gives the follwing info as usual:``` Mon Dec 2 09:46:39 2024 +-----------------------------------------------------------------------------------------+
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Mmm, then there might be some incompatibility between your CUDA version and the one in the docker image...Can you share the entire error you're getting? |
Sure. let me restart notebook and run the code again to get the error. Wil update in few minutes. |
This is the error I first got:
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Sorry the font changed, and the bold letters are not my intentional doing :) |
Thanks. The error is not due to a missing GPU, but some internal Kilosort3 failure... It could be something wrong with your data or some high levels of localized activity/noise which makes whitening failing |
hmmm...ok. I thought the whitening also had to do something with the GPU issue. What is the GPU not found error then? |
Ahh sorry I misread the error.. yeah it could be an incompatibility issue between the GPU-CUDA version on your system and the one KS was compiled against. Unfortunately, in this case the only solution would be to compile a new image with the required versions... |
ok. I will do that and see if it works. |
We don't specify any notebook version (also there are many different packages involved). If you have problems with Jupyter and spikeinterface, please open another issue about it! |
Hi,
Wondering if recent updates in Spikeinterface or docker have changed setting such that it requires GPU access now. While running kilosort3 I am getting 'Unable to find a supported GPU device' error, which I think is docker trying to access GPU and failing because pytorch is not currently installed in my 'si_env' environment.
Please confirm if that is the case or there's more to this. If GPU access is now required then I am going to install Pytorch in my environment compatible with CUDA 11.8.
Thanks
Jimmy
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