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Improve CUDA enabled images docs and add a policy (#2097)
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README.md

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@@ -101,6 +101,7 @@ more information is available in the [documentation](https://jupyter-docker-stac
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- Single-platform images have either `aarch64-` or `x86_64-` tag prefixes, for example, `quay.io/jupyter/base-notebook:aarch64-python-3.11.6`
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- Starting from `2022-09-21`, we create multi-platform images (except `tensorflow-notebook`)
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- Starting from `2023-06-01`, we create a multi-platform `tensorflow-notebook` image as well
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- Starting from `2024-02-24`, we create CUDA enabled variant of `pytorch-notebook` image for `x86_64` platform
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## Using old images
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docs/using/selecting.md

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The Jupyter team maintains a set of Docker image definitions in the <https://github.com/jupyter/docker-stacks> GitHub repository.
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The following sections describe these images, including their contents, relationships, and versioning strategy.
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## CUDA enabled variant
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We provide CUDA accelerated version of `pytorch-notebook` image.
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Prepend a CUDA version prefix (like `cuda12-`) to the image tag to allow PyTorch operations to use compatible NVIDIA GPUs for accelerated computation.
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We only build images for 2 last major versions of CUDA.
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For example, you can use an image `quay.io/jupyter/pytorch-notebook:cuda12-python-3.11.8`
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### jupyter/docker-stacks-foundation
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[Source on GitHub](https://github.com/jupyter/docker-stacks/tree/main/images/docker-stacks-foundation) |
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- Everything in `jupyter/scipy-notebook` and its ancestor images
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- [pytorch](https://pytorch.org/) machine learning library
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> **GPU Acceleration:** Append a CUDA version prefix (`cuda11-` for CUDA 11 or `cuda12-` for CUDA 12) to the image tag to allow PyTorch operations to use compatible NVIDIA GPUs for accelerated computation.
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### jupyter/datascience-notebook
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[Source on GitHub](https://github.com/jupyter/docker-stacks/tree/main/images/datascience-notebook) |

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