Enable CUDA build for ARM64 #2351
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Pull Request Overview
This pull request enables CUDA build support for ARM64 (aarch64) platforms to support hardware like NVIDIA DGX Spark systems. The changes add ARM64 CUDA build configurations for both TensorFlow and PyTorch notebooks.
- Adds
aarch64-tensorflow-cudajob for building CUDA-enabled TensorFlow notebooks on ARM64 - Adds
aarch64-pytorch-cuda12job for building CUDA-enabled PyTorch notebooks on ARM64 with CUDA 12 - Updates the
tag-pushjob dependencies to include the new ARM64 CUDA build jobs
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| aarch64-tensorflow-cuda: | ||
| uses: ./.github/workflows/docker-build-test-upload.yml | ||
| with: | ||
| parent-image: scipy-notebook | ||
| image: tensorflow-notebook | ||
| variant: cuda | ||
| platform: aarch64 | ||
| runs-on: ubuntu-24.04-arm | ||
| timeout-minutes: 25 | ||
| needs: aarch64-scipy | ||
| if: ${{ !contains(github.event.pull_request.title, '[FAST_BUILD]') }} |
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The README.md file should be updated to reflect that CUDA builds are now available for ARM64 platforms. Currently, lines 104-105 in README.md state that CUDA variants are only available for x86_64 platform, which will be inaccurate after this PR is merged.
Suggested addition to README.md around line 105:
- Starting from `2025-XX-XX`, we create CUDA enabled variants of `pytorch-notebook` and `tensorflow-notebook` images for `aarch64` platform
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replaced by #2352 |
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Enable CUDA build for ARM64
Since there are ARM64 platform like DGX spark, we need CUDA build for ARM64.
(give DGX spark case, given it requires CUDA capacity of 12.1, so latest CUDA is fine)
Checklist (especially for first-time contributors)