Adagio: Making DVS practical for complex HPC applications

Barry Rountree, David K. Lowenthal, Bronis R. De Supinski, Martin Schulz, Vincent W. Freeh, Tyler Bletsch

Research output: Chapter in Book/Report/Conference proceedingConference contribution

210 Scopus citations


Power and energy are first-order design constraints in high performance computing. Current research using dynamic voltage scaling (DVS) relies on trading increased execution time for energy savings, which is unacceptable for most high performance computing applications. We present Adagio, a novel runtime system that makes DVS practical for complex, real-world scientific applications by incurring only negligible delay while achieving signifi-cant energy savings. Adagio improves and extends previous stateof-the-art algorithms by combining the lessons learned from static energy-reducing CPU scheduling with a novel runtime mechanism for slack prediction. We present results using Adagio for two realworld programs, UMT2K and ParaDiS, along with the NAS Parallel Benchmark suite. While requiring no modification to the application source code, Adagio provides total system energy savings of 8% and 20% for UMT2K and ParaDiS, respectively, with less than 1% increase in execution time.

Original languageEnglish (US)
Title of host publicationICS'09 - Proceedings of the 23rd International Conference on Supercomputing
Number of pages10
StatePublished - 2009
Externally publishedYes
Event23rd International Conference on Supercomputing, ICS'09 - Yorktown Heights, NY, United States
Duration: Jun 8 2009Jun 12 2009

Publication series

NameProceedings of the International Conference on Supercomputing


Other23rd International Conference on Supercomputing, ICS'09
Country/TerritoryUnited States
CityYorktown Heights, NY


  • DVFS
  • DVS
  • Energy
  • MPI
  • Runtime

ASJC Scopus subject areas

  • Computer Science(all)


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