NVIDIA/cutile-python
cuTile is a programming model for writing parallel kernels for NVIDIA GPUs
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Where it stands
Rank, growth pace and release cadence relative to everything GStars tracks.
The project lists 22 contributors on GitHub.
Peaked at #93 in the weekly ranking the week of Dec 14, its best in the past year.
Use Cases & Benefits
- Provides a Python programming model for writing parallel GPU kernels targeting NVIDIA hardware.
- Enables Python developers to write efficient, tile-based parallel kernels leveraging CUDA Toolkit 13.1+ with seamless integration.
- Use for accelerating compute-intensive Python applications by offloading parallel workloads to NVIDIA GPUs.
- Use for developing custom GPU kernels in Python for scientific computing or machine learning workflows requiring fine-grained parallelism.
- Use for prototyping and testing GPU kernel logic in Python before porting to lower-level CUDA C++ implementations.
Should you depend on it?
License terms, project hygiene and risks, from GitHub metadata and GStars' snapshots.
License
Other
GitHub could not identify this license; read the LICENSE file before depending on it.
Community files
- README: present
- Contributing guide: present
Watch-outs
- License not identified by GitHub; read the LICENSE file before depending on it.
- No GitHub releases; pin a commit or tag instead of a release.
General guidance from repository metadata, not legal advice. How we score
From the README
cuTile Python is a programming language for NVIDIA GPUs. The official documentation can be found on docs.nvidia.com, or built from source located in the docs folder.
cuTile Python is published on PyPI under the cuda-tile package name and can be installed with
pip:Currently, the CUDA Toolkit 13.1+ is required and needs to be installed separately.
cuTile is written mostly in Python, but includes a C++ extension which needs to be built. You will need:
On an Ubuntu system, the first four dependencies can be installed with APT:
The CMakeLists.txt script will also automatically download the DLPack dependency from GitHub. If you wish to disable this behavior and provide your own copy of DLPack, set the
CUDA_TILE_CMAKE_DLPACK_PATHenvironment variable to a local path to the DLPack source tree.
Daily snapshots
Stars gained per day, and how forks and open issues moved, from GStars' daily snapshots
Forks
160+18
Open issues
36+11
Compared with peers in Graphics
Fastest-growing repositories GStars tracks in this cohort for the week of Nov 1, by 7-day star growth
| Repository | Stars | +7d | Health | Last release |
|---|---|---|---|---|
| heygen-com/hyperframes | 79.6K | +4.1K | 45 | today |
| mrdoob/three.js | 117.7K | +463 | 65 | 6 days ago |
| NVIDIA/cuda-rust | 4.0K | +122 | 60 | 4 days ago |
| bilawalsidhu/gods-eye-view | 61.8K | — | 60 | 3 days ago |
| processing/p5.js | 24.2K | — | 65 | 7 days ago |
| NVIDIA/cutile-python | 2.2K | — | 33 | — |
| Category median | 61.8K | +463 | 60 | — |
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