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cuPyNumeric

cuPyNumeric is a high-performance array computing library that implements the NumPy API on top of the Legate framework. It enables you to run existing NumPy workflows on GPUs and distributed systems with little to no code changes.

Whether your work involves large-scale data analysis, complex simulations, or machine learning, cuPyNumeric allows you to seamlessly scale from a single CPU, to a single GPU, and up to thousands of GPUs across multiple nodes.

Installation

Pre-built cuPyNumeric packages are available from conda on the legate channel and from PyPI. See https://docs.nvidia.com/cupynumeric/latest/installation.html for details about different install configurations, or building cuPyNumeric from source.

📌 Note

Packages are offered for Linux (x86_64 and aarch64) and macOS (aarch64, pip wheels only), supporting Python versions 3.11 to 3.13. Windows is only supported through WSL.

Documentation

The cuPyNumeric documentation can be found here.

Contributing

See the discussion on contributing in CONTRIBUTING.md.

Contact

For technical questions about cuPyNumeric and Legate-based tools, please visit the community discussion forum.

If you have other questions, please contact us at legate(at)nvidia.com.

Note

The cuPyNumeric project is independent of the CuPy project. CuPy is a trademark of Preferred Networks, Inc, and the name 'cuPyNumeric' is used with their permission.