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A NumPy-compatible array library accelerated by CUDA

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CuPy : A NumPy-compatible array library accelerated by CUDA

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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.

Installation

Wheels (precompiled binary packages) are available for Linux (x86_64) and Windows (amd64). 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
v11.2 pip install cupy-cuda112 (see #4704 for Linux instructions)

See the Installation Guide if you are using Conda/Anaconda or to build from source.

Run on Docker

Use NVIDIA Container Toolkit to run CuPy image with GPU.

$ docker run --gpus all -it cupy/cupy

More information

License

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.

Reference

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"
}

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