[dahart]

Regarding the section on Python and high-level CUDA, anyone interested should maybe first take a peek at Warp, which I’m guessing is too new to have a book yet. Warp lets you write CUDA kernels directly in Python, and it’s a breeze to get started. https://github.com/nvidia/warp

[tirutiru]

It's a bit confusing now with Numba Cuda also being officially maintained by Nvidia. Also Cuda Python, which looks older.

Which of these - warp, numba, cp, is the best bet for a beginner?

https://nvidia.github.io/numba-cuda/

https://developer.nvidia.com/cuda/python

[dahart]

I haven’t tried them all, but I suspect Warp is the easiest; it’s ridiculously easy. I’m sure there are some tradeoffs, so once you learn a little CUDA in Python it might make sense to switch from Warp to Numba or CP depending on what you’re doing.

[dandanua]

You can also write CUDA kernels directly in Julia using CUDA.jl. I basically learned CUDA programming by experimenting in Julia with the help of LLMs.