Presentation
Enhancing Performance Reproducibility on HPC Workflows
DescriptionReproducibility is related to achieving consistent performance across multiple runs of the same application in an identical computing environment. From a computational perspective, jobs should run for equal time, with equal performance repeatedly. Without this, we see significant variations in performance, which can undermine the reliability of scientific results. However, the complexity and scale of these workflows present unique challenges, especially when it comes to achieving consistent performance across repeated runs. We seek to provide researchers with Findable, Accessible, Interoperable and Reusable (FAIR) data. Ensuring the “FAIRness” of (meta)data can reduce barriers to reproducibility by making this information easier to find and interpret, programmatically access, and reuse in new contexts. Therefore we are exploring the process of analyzing performance data and seek to integrate our findings in the RECUP framework for reproducibility, showing data sources, repository saving intermediate results, and user analysis of performance and result reproducibility.
Event Type
ACM Student Research Competition: Graduate Poster
ACM Student Research Competition: Undergraduate Poster
Doctoral Showcase
Posters
TimeTuesday, 19 November 202412pm - 5pm EST
LocationB302-B305
TP
XO/EX