bkpcoding / cupy

A NumPy-compatible array library accelerated by CUDA

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 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.

Run on Docker

Use NVIDIA Container Toolkit to run CuPy image with GPU.

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

More information

• Release Notes
• Projects using CuPy
• Contribution Guide

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"
}