Presentation
Seesaw: Elastic Scaling for Task-Based Distributed Programs
DescriptionModern batch schedulers in HPC environments enable the shared use of available computational resources via provisioning discrete sets of resources matching user requirements. The lack of elasticity in such scenarios is often addressed using a Pilot job model where multiple separate requests are pooled. In this work, we explore computational elasticity in a popular Python-based workflow system: Parsl. We identify limitations in existing scaling logic and propose a new resource-aware scheduler. We show a significant improvement in the efficiency of compute resources consumed with minimal loss in time to solution.
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