# cupy
**Repository Path**: looen/cupy
## Basic Information
- **Project Name**: cupy
- **Description**: https://github.com/cupy/cupy.git
- **Primary Language**: Python
- **License**: MIT
- **Default Branch**: master
- **Homepage**: None
- **GVP Project**: No
## Statistics
- **Stars**: 0
- **Forks**: 0
- **Created**: 2020-01-07
- **Last Updated**: 2021-04-25
## Categories & Tags
**Categories**: Uncategorized
**Tags**: None
## README
# CuPy : NumPy-like API accelerated with CUDA
[](https://pypi.python.org/pypi/cupy)
[](https://github.com/cupy/cupy)
[](https://travis-ci.org/cupy/cupy)
[](https://coveralls.io/github/cupy/cupy)
[](https://docs-cupy.chainer.org/en/stable/)
[**Website**](https://cupy.chainer.org/)
| [**Docs**](https://docs-cupy.chainer.org/en/stable/)
| [**Install Guide**](https://docs-cupy.chainer.org/en/stable/install.html)
| [**Tutorial**](https://docs-cupy.chainer.org/en/stable/tutorial/)
| **Examples** ([Official](https://github.com/cupy/cupy/tree/master/examples))
| **Forum** ([en](https://groups.google.com/forum/#!forum/cupy), [ja](https://groups.google.com/forum/#!forum/cupy-ja))
*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.
## Installation
For detailed instructions on installing CuPy, see [the installation guide](https://docs-cupy.chainer.org/en/stable/install.html).
You can install CuPy using `pip`:
```sh
(Binary Package for CUDA 8.0)
$ pip install cupy-cuda80
(Binary Package for CUDA 9.0)
$ pip install cupy-cuda90
(Binary Package for CUDA 9.1)
$ pip install cupy-cuda91
(Binary Package for CUDA 9.2)
$ pip install cupy-cuda92
(Binary Package for CUDA 10.0)
$ pip install cupy-cuda100
(Binary Package for CUDA 10.1)
$ pip install cupy-cuda101
(Source Package)
$ pip install cupy
```
The latest version of cuDNN and NCCL libraries are included in binary packages (wheels).
For the source package, you will need to install cuDNN/NCCL before installing CuPy, if you want to use it.
## Run with Docker
We provide the official Docker image.
Use [nvidia-docker](https://github.com/NVIDIA/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
```
## Development
Please see [the contribution guide](https://docs-cupy.chainer.org/en/stable/contribution.html).
## More information
- [Release notes](https://github.com/cupy/cupy/releases)
- [Projects using CuPy](https://github.com/cupy/cupy/wiki/Projects-using-CuPy)
## License
MIT License (see `LICENSE` file).
CuPy is designed based on NumPy's API and SciPy's API (see `docs/LICENSE_THIRD_PARTY` file).
## 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](http://learningsys.org/nips17/assets/papers/paper_16.pdf)
```
@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"
}
```