Original upload date: Sat, 12 May 2018 00:00:00 GMT
Archive date: Mon, 29 Nov 2021 04:43:14 GMT
Speaker: Shohei Hido
![Logo][https://raw.githubusercontent.com/cupy/cupy/master/docs/image/cupy_logo_1000px.png]
# CuPy : NumPy-like API accelerated with CUDA
[**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/blob/master/examples)) | [**Forum**](https://groups.google.com/forum/#!forum/cupy)
CuPy is an open-source library with NumPy syntax that increases speed by doing matrix operations on NVIDIA GPUs. It is accelerated with the CUDA platform from NVIDIA and also uses CUDA-related libraries, including cuBLAS, cuDNN, cuRAND, cuSOLVER, cuSPARSE, and NCCL, to make full use of the GPU architecture. CuPy's interface is highly compatible with NumPy; in most cases it can be used as a drop-in replacement. CuPy supports various methods, data types, indexing, broadcasting, and more.
Slides can be found at: https://speakerdeck.com/pycon2018 and https://github.com/PyCon/2018-slides
