Power limits on future high-performance computing (HPC) systems will constrain applications. However, HPC applications do not consume constant power over their lifetimes. Thus, applications assigned a fixed power bound may be forced to slow down during high-power computation phases, but may not consume their full power allocation during low-power I/O phases. This paper explores algorithms that leverage application semantics-phase frequency, duration and power needs-to shift unused power from applications in I/O phases to applications in computation phases, thus improving system-wide performance. We design novel techniques that include explicit staggering of applications to improve power shifting. Compared to executing without power shifting, our algorithms can improve average performance by up to 8% or improve performance of a single, high-priority application by up to 32%.
Identifer | oai:union.ndltd.org:arizona.edu/oai:arizona.openrepository.com:10150/622666 |
Date | 05 1900 |
Creators | Savoie, Lee, Lowenthal, David K., Supinski, Bronis R. de, Islam, Tanzima, Mohror, Kathryn, Rountree, Barry, Schulz, Martin |
Contributors | Dept. of Comput. Sci., Univ. of Arizona |
Publisher | IEEE |
Source Sets | University of Arizona |
Language | English |
Detected Language | English |
Type | Article |
Rights | Copyright © 2016, IEEE |
Relation | http://ieeexplore.ieee.org/document/7516070/ |
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