MPIAnnealing: distribute statistics to all workers#19
Open
lijun99 wants to merge 1 commit intoAlTarFramework:masterfrom
Open
MPIAnnealing: distribute statistics to all workers#19lijun99 wants to merge 1 commit intoAlTarFramework:masterfrom
lijun99 wants to merge 1 commit intoAlTarFramework:masterfrom
Conversation
aivazis
reviewed
Aug 22, 2019
Member
aivazis
left a comment
There was a problem hiding this comment.
Why is it important for each worker to see the resampling statistics? If i'm not mistaken, the manager rescales the covariance matrix and then publishes to everybody. Is this a feature you need for an extension to the current altar algorithms?
Contributor
Author
|
That will also work; but is not being done in current code. |
This file contains hidden or bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment
Add this suggestion to a batch that can be applied as a single commit.This suggestion is invalid because no changes were made to the code.Suggestions cannot be applied while the pull request is closed.Suggestions cannot be applied while viewing a subset of changes.Only one suggestion per line can be applied in a batch.Add this suggestion to a batch that can be applied as a single commit.Applying suggestions on deleted lines is not supported.You must change the existing code in this line in order to create a valid suggestion.Outdated suggestions cannot be applied.This suggestion has been applied or marked resolved.Suggestions cannot be applied from pending reviews.Suggestions cannot be applied on multi-line comments.Suggestions cannot be applied while the pull request is queued to merge.Suggestion cannot be applied right now. Please check back later.
The bcast the statistics (acceptance/rejection) to all workers was missing; therefore only the master thread updated the scaling.
With the newly added MPI_Allreduce to pyre, this is now done in an easier way.