GPU-Optional Python

GPU-Optional Python

Write code that exploits a GPU when available and desirable, but that runs fine on your CPUs when not

The wonderful CuPy library allows you to easily run NumPy-compatible code on a NVIDIA GPU. However, sometimes

  • you (or your users) don’t have a compatible GPU, or
  • you don’t have a CuPy-compatible Python environment, or
  • your code runs slower on our GPU than on your multiple CPUs.

By defining three simple utility functions, you can make your code _GPU-optional. (_Find the utility functions’ definitions in this small GitHub project.)

data-science python gpu

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