Application-aware management of parallel simulation collections

This paper presents a system deployed on parallel clusters to manage a collection of parallel simulations that make up a computational study. It explores how such a system can extend traditional parallel job scheduling and resource allocation techniques to incorporate knowledge specific to the study. Using a UINTAH-based helium gas simulation code (ARCHES) and the SimX system for multi-experiment computational studies, this paper demonstrates that, by using application-specific knowledge in resource allocation and scheduling decisions, one can reduce the run time of a computational study from over 20 hours to under 4.5 hours on a 32-processor cluster, and from almost 11 hours to just over 3.5 hours on a 64-processor cluster. Categories and Subject Descriptors D.4.7 [Operating Systems]: Organization and Design--Batch processing systems, Distributed systems, Hierarchical design; C.5.m [Computer System Organization]: Computer System Implementation--Miscellaneous General Terms Design, Per...

• Type: Conference
• Year: 2009
• Where: PPOPP
• Authors: Siu Yau, Vijay Karamcheti, Denis Zorin, Kostadin Damevski, Steven G. Parker
• Keywords: Computer System Organization, Keywords Parallel System, Parallel Computing, Parallel Job Scheduling, PPOPP 2009