Add GKE A3 Ultra support #940
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samos123
commented
Jan 22, 2025
samos123
commented
- Adds support for easily adding more GKE GPU accelerators by using a base class
- Adds Fuji v2 70B benchmark results
samos123
commented
Jan 22, 2025
Dockerfile
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| @@ -101,14 +93,63 @@ COPY . . | |||
| # GPU container spec. # | |||
| ################################################################################ | |||
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| FROM base AS gpu | |||
| # This causes INTERNAL: No valid engine configs for Matmul error | |||
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@markblee @kelvin-zou are you fine with moving to nvidia/cuda:12.6.3-cudnn-devel-ubuntu22.04 as the base image. I couldn't get A3 Ultra working on the original python base image.
samos123
commented
Jan 22, 2025
Dockerfile
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| # TODO(markblee): Support extras. | ||
| ENV PIP_FIND_LINKS=https://storage.googleapis.com/jax-releases/jax_cuda_releases.html | ||
| RUN pip install .[core,gpu] | ||
| COPY . . | ||
| RUN pip install -U "jax[gpu]==0.4.38" "jax==0.4.38" "jaxlib==0.4.38" \ |
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TODO: this should be removed. Maybe we should wait until axlearn main upgrades to 0.4.38.
ruomingp
reviewed
Jan 22, 2025
| # So we're using the NVIDIA provided cuda image instead which works. | ||
| FROM nvidia/cuda:12.6.3-cudnn-devel-ubuntu22.04 as gpu | ||
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| # Copy from original base |
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Does it mean that we will need to keep the following commands consistent with those in BASE? Does Dockerfile support functions?
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| # Using `FROM base as GPU` causes INTERNAL: No valid engine configs for Matmul error. | ||
| # So we're using the NVIDIA provided cuda image instead which works. | ||
| FROM nvidia/cuda:12.6.3-cudnn-devel-ubuntu22.04 as gpu |
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Let's make sure this change doesn't break our GPU training on AWS.
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