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NVIDIA GPU direct storage #51
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Yeah, any way to easily verify this? Maybe @quasiben has an idea what hardware / networking combination might work? |
There's this script https://github.com/rapidsai/kvikio/blob/29c52f76035002d91f301895250c0ff14f18f50a/python/benchmarks/single-node-io.py to check for GDS compatibility. MIght need to install a few other packages to fix ImportErrors, but the gist is:
These are the results I got on Microsoft Planetary Computer Pytorch container (copied from xarray-contrib/xbatcher#87 (comment)):
I don't have sudo permissions, but if you have time, maybe try |
Unfortunately, I don't think GDS is supported on cloud infra (even with mounted NVMe) but the GDS team is working on it. @cnewburn can you comment with additional thoughts ? |
I spoke with GDS team and they are working on addressing this issue. We expect this to be available in next CUDA release |
Hi there,
Was thinking if it's possible to enable NVIDIA GPU Direct Storage on Microsoft Planetary Computer? This could enable reading Zarr files directly into GPU memory from cloud storage, and we'd be excited to have a demo use-case running (xref xarray-contrib/xbatcher#87).
Packages that need to be installed:
References:
Might need to check if the Azure cluster supports GPU direct storage first, but if it does, I can open up PRs to add these into the Pytorch and/or Tensorflow containers 😄
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