CuPy
# CuPy

CuPy is an open source library for GPU-accelerated computing with Python programming language, providing support for multi-dimensional arrays, sparse matrices, and a variety of numerical algorithms implemented on top of them. CuPy shares the same API set as NumPy and SciPy, allowing it to be a drop-in replacement to run NumPy/SciPy code on GPU. CuPy supports NVIDIA CUDA GPU platform, and AMD ROCm GPU platform starting in v9.0.

CuPy has been initially developed as a backend of Chainer deep learning framework, and later established as an independent project in 2017.

CuPy is a part of the NumPy ecosystem array libraries and is widely adopted to utilize GPU with Python, especially in high-performance computing environments such as Summit, Perlmutter, EULER, and ABCI.

CuPy is a NumFOCUS affiliated project.

## Features

CuPy implements NumPy/SciPy-compatible APIs, as well as features to write user-defined GPU kernels or access low-level APIs.

### NumPy-compatible APIs

The same set of APIs defined in the NumPy package (numpy.*) are available under cupy.* package.

* Multi-dimensional array (cupy.ndarray) for boolean, integer, float, and complex data types
* Module-level functions
* Linear algebra functions
* Fast Fourier transform
* Random number generator

### SciPy-compatible APIs

The same set of APIs defined in the SciPy package (scipy.*) are available under cupyx.scipy.* package.

* Sparse matrices (cupyx.scipy.sparse.*_matrix) of CSR, COO, CSC, and DIA format
* Discrete Fourier transform
* Advanced linear algebra
* Multidimensional image processing
* Sparse linear algebra
* Special functions
* Signal processing
* Statistical functions

### User-defined GPU kernels

* Kernel templates for element-wise and reduction operations
* Raw kernel (CUDA C/C++)
* Just-in-time transpiler (JIT)
* Kernel fusion

### Distributed computing

* Distributed communication package (cupyx.distributed), providing collective and peer-to-peer primitives

### Low-level CUDA features

* Stream and event
* Memory pool
* Profiler
* Host API binding
* CUDA Python support

### Interoperability

* DLPack
* CUDA Array Interface
* NEP 13 (__array_ufunc__)
* NEP 18 (__array_function__)
* Array API Standard

## Applications

* spaCy
* XGBoost
* turboSETI (Berkeley SETI)
* NVIDIA RAPIDS
* einops
* Chainer
