What is CuPy?
It is an open-source matrix library accelerated with NVIDIA CUDA. CuPy provides GPU accelerated computing with Python. It uses CUDA-related libraries including cuBLAS, cuDNN, cuRand, cuSolver, cuSPARSE, cuFFT and NCCL to make full use of the GPU architecture.
CuPy is a tool in the Data Science Tools category of a tech stack.
CuPy is an open source tool with 4.2K GitHub stars and 377 GitHub forks. Here’s a link to CuPy's open source repository on GitHub
Pros of CuPy
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- It's interface is highly compatible with NumPy in most cases it can be used as a drop-in replacement
- Supports various methods, indexing, data types, broadcasting and more
- You can easily make a custom CUDA kernel if you want to make your code run faster, requiring only a small code snippet of C++
- It automatically wraps and compiles it to make a CUDA binary
- Compiled binaries are cached and reused in subsequent runs
CuPy Alternatives & Comparisons
What are some alternatives to CuPy?
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