8000 ENH: SIMD architectures to show_config by ganesh-k13 · Pull Request #19130 · numpy/numpy · GitHub
[go: up one dir, main page]
Skip to content

ENH: SIMD architectures to show_config #19130

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.

Sign up for GitHub

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

Jump to bottom
Merged
merged 1 commit into from
May 29, 2021
Merged

ENH: SIMD architectures to show_config #19130

merged 1 commit into from
May 29, 2021

Conversation

ganesh-k13
Copy link
Member
@ganesh-k13 ganesh-k13 commented May 28, 2021 •
edited by rgommers
Loading

Changes:

Added SIMD dispatch information in np.show_config

Closes gh-18490

Sample output:

>>> np.show_config()
.
.
.
Supported SIMD extensions in this NumPy install:
    baseline = SSE,SSE2,SSE3
    found = SSSE3,SSE41,POPCNT,SSE42,AVX,F16C,FMA3,AVX2
    not found = AVX512F,AVX512CD,AVX512_KNL,AVX512_KNM,AVX512_SKX,AVX512_CLX,AVX512_CNL,AVX512_ICL

Note: Not sure about changes in np.distutils.cpuinfo, I can add in the same PR with a bit more info.

rgommers
rgommers approved these changes May 29, 2021
View reviewed changes
Copy link
Member
@rgommers rgommers left a comment

Choose a reason for hiding this comment

The reason will be displayed to describe this comment to others. Learn more.

This looks good, thanks @ganesh-k13.

Note: Not sure about changes in np.distutils.cpuinfo, I can add in the same PR with a bit more info.

Let's treat that as a separate issue, because that's much more involved and not just about more clearly showing information. I'm also wary of spending time on any numpy.distutils component, since that may be partly wasted effort given that I'm trying to move us away from it at the moment.

@rgommers rgommers merged commit 565cb73 into numpy:main May 29, 2021
@ganesh-k13
Copy link
Member Author

Thanks, Ralf!

@mattip
Copy link
Member
mattip commented Jun 30, 2021

This seems to have just missed the cut for 1.21. Could we backport it? It would make debugging things like conda-forge/numpy-feedstock#237 easier since it seems the CI machines vary.

@mattip
Copy link
Member
mattip commented Jun 30, 2021

@charris ^^^

@h-vetinari
Copy link
Contributor

Hey @mattip, no need to backport IMO, I can use the private API for the moment - e.g. we used the following to debug conda-forge/numpy-feedstock#235:

python -c 'import numpy; numpy._pytesttester._show_numpy_info()'

@h-vetinari
Copy link
Contributor

PS: not that I'm against a backport, of course - it would help a little for sure. :)

@charris charris added the 09 - Backport-Candidate PRs tagged should be backported label Jun 30, 2021
@charris charris added this to the 1.21.1 release milestone Jun 30, 2021
@charris
Copy link
Member
charris commented Jun 30, 2021

@mattip No problem.

@charris charris mentioned this pull request Jul 1, 2021
Merged
@charris charris removed the 09 - Backport-Candidate PRs tagged should be backported label Jul 1, 2021
@charris charris removed this from the 1.21.1 release milestone Jul 1, 2021
@rgommers rgommers added the component: SIMD Issues in SIMD (fast instruction sets) code or machinery label Jul 12, 2022
Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment
Reviewers

@rgommers rgommers rgommers approved these changes

Assignees
No one assigned
Labels
01 - Enhancement component: SIMD Issues in SIMD (fast instruction sets) code or machinery
Projects
None yet
Milestone
No milestone
Development

Successfully merging this pull request may close these issues.

Hard to discover what SIMD architectures numpy was compiled with
5 participants
@ganesh-k13 @mattip @h-vetinari @charris @rgommers
0