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

Consolidated accel and sum into Vector4 #369

Merged
merged 2 commits into from
Oct 14, 2024

Conversation

gregjesl
Copy link
Contributor

Summary

Updated harmonics calculations using Vector4

Architectural Changes

No change

New Features

No change

Improvements

Leveraged Vector4 for acceleration and sum terms of Pines' algorithm. Slight performance improvement expected.

No change

Bug Fixes

No change

Testing and validation

All tests passing

Documentation

This PR does not primarily deal with documentation changes.

@gregjesl
Copy link
Contributor Author

Found an issue, closing pull request. Will reopen if/when fixed.

@gregjesl gregjesl closed this Oct 14, 2024
@ChristopherRabotin
Copy link
Member

That's a useful change, thanks! I'll be happy to review and merge it quickly when you're content with the proposed change.

@gregjesl
Copy link
Contributor Author

Found the issue - I missed the -= hiding in there...

@gregjesl gregjesl reopened this Oct 14, 2024
@gregjesl
Copy link
Contributor Author

gregjesl commented Oct 14, 2024

My goal is to implement a multi-threaded version of Pines' algorithm, now I can throw a std::sync::mutex around accel4 and farm out the calculations. Once I get that done I'll open a separate pull request.

@gregjesl
Copy link
Contributor Author

Forgot to mention: I found the issue and tested the fix by running the LRO example. Now the results are the same.

@ChristopherRabotin
Copy link
Member

Thanks for the quick turn around! I'll go ahead and merge this.

Multithreading the Pines algorithm probably won't improve the computational speed. I've been keeping an eye on @MartinAstro 's work on physics informed neural networks for the past few years: https://github.com/MartinAstro/GravNN . The first iteration of this model shows impressive performance improvements compared to the typical algorithms, including Pines. The subsequent versions of his work improve the quality of the solution even when far from the central object. I'll reach out to assess the complexity in implementing this in Nyx.

@ChristopherRabotin ChristopherRabotin merged commit b488863 into nyx-space:master Oct 14, 2024
10 checks passed
Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment
Labels
None yet
Projects
None yet
Development

Successfully merging this pull request may close these issues.

2 participants