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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.
It supports a subset of numpy.ndarray
interface.
For detailed instructions on installing CuPy, see the installation guide.
You can install CuPy using pip
:
$ pip install cupy
Note that if you want to enable CUDA, cuDNN, and/or NCCL, they need to be set up before installation of CuPy.
We provide the official Docker image. Use nvidia-docker command to run CuPy image with GPU. You can login to the environment with bash, and run the Python interpreter.
$ nvidia-docker run -it cupy/cupy /bin/bash
Please see the contribution guide.
MIT License (see LICENSE
file).
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"
}