Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Exploring GPU acceleration using CuPy for enhanced performance #85

Closed
zjzjwang opened this issue Apr 17, 2024 · 2 comments
Closed

Exploring GPU acceleration using CuPy for enhanced performance #85

zjzjwang opened this issue Apr 17, 2024 · 2 comments
Labels

Comments

@zjzjwang
Copy link

Thank you for your excellent work.

I am considering whether it would be feasible to further accelerate the process using a GPU (such as CuPy).

As mentioned in #63 , using CuPy should speed up some operators, but my implementation did not observe a significant speed increase (in fact, it significantly decreased). (I simply replaced numpy with cupy in aggregate_numpy.py )

Do you have some ideas on implementations on GPU?

@ml31415
Copy link
Owner

ml31415 commented Apr 17, 2024

Hi @zjzjwang We only had this PR so far, you probably saw it: #63 . The problem with this algorithm is, that it is hard to parallelize. Which is, what the GPU would be good for. See here for approaches for further parallelization: https://github.com/xarray-contrib/flox

@zjzjwang
Copy link
Author

Thanks for the feedback, @ml31415 .

I'll check out the link you provided. We can close this issue now.

@ml31415 ml31415 closed this as not planned Won't fix, can't repro, duplicate, stale Apr 17, 2024
Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment
Labels
Projects
None yet
Development

No branches or pull requests

2 participants