CUDA Python vs PyCUDA


I checked the past questions, but I couldn’t solve them, so I will ask.
There are two CUDA wrappers, pyCUDA and CUDA-Python. Which should I use?

I would be grateful if you could tell me about the differences.

Both CUDA-Python and pyCUDA allow you to write GPU kernels using CUDA C++. The kernel is presented as a string to the python code to compile and run.

The key difference is that the host-side code in one case is coming from the community (Andreas K and others) whereas in the CUDA Python case it is coming from NVIDIA. There are syntactical differences of course, but you should be able to perform basic operations using either methodology.

CUDA Python allows for the possibility to have a “standardized” host api/interface, while still being able to use other methodologies such as Numba to enable (for example) the writing of kernel code in python.

This blog and the questions that follow it may be of interest.

FWIW there are other python/CUDA methodologies. numba, cupy, CUDA python, and pycuda are some of the available approaches to tap into CUDA acceleration from Python. CUDA Python can interoperate with most or all of them.


Good morning.
I got up in the morning and got an answer and am excited!!

I understand the difference between pyCUDA and CUDA-Python.
I will investigate a little more based on this content.
Thank you!

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