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CuPy is an implementation of NumPy-compatible multi-dimensional array on CUDA.
CuPy consists of the core multi-dimensional array class, cupy.ndarray, and many functions on it.
Wheels (precompiled binary packages) are available for Linux and Windows. Choose the right package for your CUDA Toolkit version.
| CUDA | Command |
|---|---|
| v9.0 | pip install cupy-cuda90 |
| v9.2 | pip install cupy-cuda92 |
| v10.0 | pip install cupy-cuda100 |
| v10.1 | pip install cupy-cuda101 |
| v10.2 | pip install cupy-cuda102 |
| v11.0 | pip install cupy-cuda110 |
| v11.1 | pip install cupy-cuda111 |
See the Installation Guide if you are using Conda/Anaconda or to build from source.
Use NVIDIA Container Toolkit to run CuPy image with GPU.
$ docker run --gpus all -it cupy/cupy
MIT License (see LICENSE file).
CuPy is designed based on NumPy's API and SciPy's API (see docs/LICENSE_THIRD_PARTY file).
CuPy is being maintained and developed by Preferred Networks Inc. and community contributors.
Ryosuke Okuta, Yuya Unno, Daisuke Nishino, Shohei Hido and Crissman Loomis. CuPy: A NumPy-Compatible Library for NVIDIA GPU Calculations. Proceedings of Workshop on Machine Learning Systems (LearningSys) in The Thirty-first Annual Conference on Neural Information Processing Systems (NIPS), (2017). URL
@inproceedings{cupy_learningsys2017,
author = "Okuta, Ryosuke and Unno, Yuya and Nishino, Daisuke and Hido, Shohei and Loomis, Crissman",
title = "CuPy: A NumPy-Compatible Library for NVIDIA GPU Calculations",
booktitle = "Proceedings of Workshop on Machine Learning Systems (LearningSys) in The Thirty-first Annual Conference on Neural Information Processing Systems (NIPS)",
year = "2017",
url = "http://learningsys.org/nips17/assets/papers/paper_16.pdf"
}