Shared Resource Sensitivity in Task-Based Runtime Systems
2013 (English)In: Proceedings of the 6th Swedish Workshop on Multi-Core Computing, Halmstad, Sweden: Halmstad University , 2013Conference paper (Refereed)
Task-based programming methodologies have become a popular alternative to explicit threading because they leave most of the complexity of scheduling and load balancing to the runtime system. Modern task schedulers use task execution information to build models which they can then use to predict future task performance and produce better schedules. However, while shared resource sensitivity, such as the use of shared cache, is widely known to hurt performance, current schedulers do not address this in their scheduling.This work applies low-overhead techniques for measuring resource sensitivity to task-based runtime systems to profile individual task behavior.We present results for several benchmarks, both in an isolated environment (all resources available) and in normal contention scenarios, and establish a direct quantitative cor-relation between individual tasks and the entire application sensitivity.We present insight into areas where these profiling techniques could enable significant gains in performance due to better scheduling, and conclude what scenarios are necessary for such improvements.
Place, publisher, year, edition, pages
Halmstad, Sweden: Halmstad University , 2013.
Resource Sharing, Tasks, Performance
Research subject Computer Science; Computer Systems
IdentifiersURN: urn:nbn:se:uu:diva-212780OAI: oai:DiVA.org:uu-212780DiVA: diva2:679219
MCC13; Sixth Swedish Workshop on Multicore Computing; 25-26 November 2013; Halmstad, Sweden
ProjectsResource Sharing ModelingUPMARC
FunderSwedish Research Council