# RFC: Moving the CUDA target to a new package maintained by NVIDIA **URL:** \ **Category:** Announcements\ **Created:** [July 3, 2024, 1:17pm UTC](https://numba.discourse.group/t/rfc-moving-the-cuda-target-to-a-new-package-maintained-by-nvidia/2628 "2024-07-03T13:17:21Z")\ **Posts on this page:** 4\ **Page:** 1
**Author:** ![gmarkall](https://yyz2.discourse-cdn.com/free1/user_avatar/numba.discourse.group/gmarkall/32/42_2.png) [@gmarkall](https://numba.discourse.group/u/gmarkall)\ **Post date:** [July 3, 2024, 1:17pm UTC](https://numba.discourse.group/t/rfc-moving-the-cuda-target-to-a-new-package-maintained-by-nvidia/2628/1 "2024-07-03T13:17:21Z")
Hi all, Presently Numba’s CUDA target is part of Numba itself, in the [`numba.cuda` module](https://github.com/numba/numba/tree/main/numba/cuda) - however, we’re planning to move it into a separate package maintained by NVIDIA, and would like to share the plans and ask for community feedback and suggestions. ## What is happening? Many things will remain the same: - No code changes should be necessary to use the separate package - existing code using `numba.cuda` will continue to work unmodified. - Using the built-in `numba.cuda` module will also continue to work, so existing (or new) environments that do not include the `numba-cuda` package will continue to work. - Development of the CUDA target will continue to be open source, though hosted on the NVIDIA Github organization rather than inside the main Numba repository. From a user perspective, the changes will be: - The existing `numba.cuda` module will remain in Numba for a considerable length of time (possibly indefinitely) but will cease to receive new feature development and eventually be deprecated. Bug fixes to this “upstream” `numba.cuda` module will be considered on a case-by-case basis. - New feature development and bug fixing will proceed in the [NVIDIA/numba-cuda repository](https://github.com/NVIDIA/numba-cuda) / package. - To use the new NVIDIA package, it will need to be installed (e.g. with `conda install numba-cuda` or `pip install numba-cuda`) but no other changes would be needed. ## Why are you doing this? We (Numba maintainers at Anaconda and NVIDIA) would like to do this because we think it will speed up the development and release cycle of the CUDA target and reduce the burden across the maintainers: - New releases of the CUDA target will be made independently of Numba’s release schedule - the release process for the CUDA target alone will be more lightweight than the Numba release process, so releases will be made on a frequent basis. - PR reviews and testing will be conducted independently of the review process for Numba PRs - this will lessen the burden on Anaconda maintainers and the Anaconda buildfarm, and will speed up the review / test time, as the Anaconda buildfarm requires manual operation and feedback to PR authors. - In summary: this will enable the CUDA target to integrate new features more quickly, and to make them generally available through releases sooner after them being merged. ## How will this work? The broad steps in the near term are: - Creation of the `numba_cuda` package: - A new `numba_cuda` package will be created, containing a copy of the CUDA target as of Numba 0.60. - The numba\_cuda package will install a “redirector” that redirects any import of the `numba.cuda` module to the version contained within the `numba_cuda` package. - Users can start installing `numba_cuda` at this point to get the benefit of new features and bug fixes added to the `numba_cuda` package. - Numba point-release: A point release following the last major Numba release will be created, incorporating the following changes: - At import time, it will try to obtain `numba.cuda` from the `numba_cuda` package, so that the redirector is no longer necessary. - It will report on the version of the CUDA target used (either the built-in one or the NVIDIA one) in the sysinfo tool, so that users can easily tell which is in use (and to help direct bug reports). In addition to the repository and packages, there are other items to address as part of this migration: - Documentation: The CUDA target documentation sources will be moved to the `numba-cuda` repository, and rendered versions of these will be published / hosted by NVIDIA. - The CUDA Array Interface specification is also part of the Numba CUDA documentation. It will be part of `numba-cuda`’s documentation initially, but should eventually be migrated elsewhere and managed independently of Numba, as it is a standard independent of any particular tool or library. - Issues: There are ~175 open CUDA issues in Numba. The migration presents an excellent opportunity to triage and review them all, and to move those that are still relevant over to `numba-cuda`, and to close those that are now resolved / no longer relevant. ## What do I (the reader) need to do? - **I maintain a package that uses `numba.cuda`:** Nothing is required - your code should continue working as it did before, whether your users use the builtin CUDA target or install the `numba-cuda` version. - Caveat: if you want to make use of new features or rely on bug fixes that go into `numba-cuda`, you will need to use it and have it as a dependency. This should not adversely affect your users, as `numba-cuda` should be fully compatible with all existing code. - **I use `numba.cuda` in my application:** Similarly for maintainers, you do not need to change your code. If you want to make use of features added to `numba-cuda`, you will need to add it as a dependency, again without the expectation of any issues / incompatibilities being created. - **I contribute to Numba and/or the CUDA target:** - I’ll reach out to anyone who has an open PR relevant to CUDA about whether to migrate the PR to the numba-cuda repository in due course. In the short term: - Feedback on the plan and questions from all users will be appreciated - please do post thoughts in the thread in response to this post! - If you have questions, please ask them - I’ve tried to cover the essentials in this post without making it overly long, so some details may be overlooked. - Please try the `numba-cuda` package in your environment and report any issues using the package or installation troubles that arise. The package can be installed with: - Conda: `conda install nvidia::numba-cuda` - Pip: `pip install numba-cuda` ## Links / references: - **Repository:** The `numba-cuda` repository in the NVIDIA Github organization: [https://github.com/NVIDIA/numba-cuda](https://github.com/NVIDIA/numba-cuda) - This will be updated as issues are discovered / resolved, with the aim of first perfectly reproducing the functionality of the built-in CUDA target. - Once the functionality is stable, new features and bug fixes will be added here. - **Redirector:** The redirector is implemented in [`_numba_cuda_redirector.py`](https://github.com/NVIDIA/numba-cuda/blob/main/site-packages/_numba_cuda_redirector.py). - **Packages:** : - Conda: `conda install nvidia::numba-cuda` / [Anaconda.org](https://anaconda.org/nvidia/numba-cuda) - Pip: `pip install numba-cuda` / [numba-cuda · PyPI](https://pypi.org/project/numba-cuda/) - **Documentation:** [https://nvidia.github.io/numba-cuda/](https://nvidia.github.io/numba-cuda/) - note this is very very similar to the existing documentation for the CUDA target 🙂 ---
**Author:** ![seanlaw](https://yyz2.discourse-cdn.com/free1/user_avatar/numba.discourse.group/seanlaw/32/506_2.png) [@seanlaw](https://numba.discourse.group/u/seanlaw)\ **Post date:** [July 10, 2024, 11:54am UTC](https://numba.discourse.group/t/rfc-moving-the-cuda-target-to-a-new-package-maintained-by-nvidia/2628/2 "2024-07-10T11:54:58Z")
Thanks for notifying us, @gmarkall! > - To use the new NVIDIA package, it will need to be installed (e.g. with `conda install numba-cuda` or `pip install numba-cuda`) but no other changes would be needed. So, I understand that things are moving over to the `NVIDIA/numba-cuda` package but will the `numba/numba` package be adding the `NVIDIA/numba-cuda` package as a dependency? In other words, I won’t need to explicitly add the `NVIDIA/numba-cuda` package to the `stumpy`’s `requirements.txt`/`environment.yml`? Currently, `stumpy` only depends on `numpy`, `scipy`, and `numba`. ---
**Author:** ![gmarkall](https://yyz2.discourse-cdn.com/free1/user_avatar/numba.discourse.group/gmarkall/32/42_2.png) [@gmarkall](https://numba.discourse.group/u/gmarkall)\ **Post date:** [August 1, 2024, 10:01am UTC](https://numba.discourse.group/t/rfc-moving-the-cuda-target-to-a-new-package-maintained-by-nvidia/2628/3 "2024-08-01T10:01:22Z")
> [@seanlaw](#): > > So, I understand that things are moving over to the `NVIDIA/numba-cuda` package but will the `numba/numba` package be adding the `NVIDIA/numba-cuda` package as a dependency? Initially I think `numba` won’t add `numba-cuda` as a dependency, but we would probably do that in future. Note that even with only `numba` installed, all existing code will continue to work because the `numba.cuda` package is not being removed from `numba`, it’s only overridden by `numba-cuda` when `numba-cuda` is installed. > [@seanlaw](#): > > In other words, I won’t need to explicitly add the `NVIDIA/numba-cuda` package to the `stumpy`’s `requirements.txt`/`environment.yml`? You won’t need to change anything right away. However, if there are changes in `numba-cuda` in future that you’d like to make use of in `stumpy`, then you would need to add `numba-cuda` as a dependency, if at that time `numba` has not added it as a dependency. ---
**Author:** ![gmarkall](https://yyz2.discourse-cdn.com/free1/user_avatar/numba.discourse.group/gmarkall/32/42_2.png) [@gmarkall](https://numba.discourse.group/u/gmarkall)\ **Post date:** [August 1, 2024, 10:07am UTC](https://numba.discourse.group/t/rfc-moving-the-cuda-target-to-a-new-package-maintained-by-nvidia/2628/4 "2024-08-01T10:07:45Z")
`numba-cuda` packages are now available - please try them out in your environment and report any issues on the [`numba-cuda` issue tracker](https://github.com/NVIDIA/numba-cuda/issues) or post back here for further discussion. Install with conda: ```bash conda install nvidia::numba-cuda ``` Install with pip: ```bash pip install numba-cuda ``` A conda-forge recipe / package is still forthcoming. CC [@RC\_Testers](https://numba.discourse.group/groups/rc_testers) - if you use CUDA, please do try these packages out.