Presentation
Interactive and Tool-Agnostic ML-Driven Workflow for Automated HPC Performance Modeling
DescriptionThis work presents an automated, reproducible, ML-based performance modeling workflow for HPC systems. The proposed workflow fully automates data generation, preprocessing, ML model training and validation. Since the proposed approach is generic and not tailored to a specific application, our workflow can be utilized for performance modeling across a wide range of performance domains. The prototype implementation is based on the JUBE workflow environment, through which a user-friendly interactive console is realized. The effectiveness of the automated workflow is demonstrated with a case study on I/O bandwidth modeling and prediction.
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