CuPy is an open source implementation of NumPy-compatible multi-dimensional array accelerated with NVIDIA CUDA. It consists of cupy.ndarray, a core multi-dimensional array class and many functions on it.
CuPy offers GPU accelerated computing with Python, using CUDA-related libraries to fully utilize the GPU architecture. According to benchmarks, it can even speed up some operations by more than 100X. CuPy is highly compatible with NumPy, serving as a drop-in replacement in most cases.
CuPy is very easy to install through pip or through precompiled binary packages called wheels for recommended environments. It also makes writing a custom CUDA kernel very easy, requiring only a small code snippet of C++.
Features
- GPU accelerated computing with Python
- Highly compatible with NumPy
- Easy installation
- Easy creation of a custom CUDA kernel
Project Samples
Categories
LibrariesLicense
MIT License
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