Towards energy efficient scaling of scientific codes

Yang Ding, Konrad Malkowski, Padma Raghavan, Mahmut Kandemir

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

11 Scopus citations

Abstract

Energy consumption is becoming a crucial concern within the high performance computing community as computers expand to the peta-scale and beyond. Although the peak execution rates on tuned dense matrix operations in supercomputers have consistently increased to approach the peta-scale regime, the linear scaling of peak execution rates has been achieved at the expense of cubic growth in power with systems already appearing in the megawatt range. In this paper, we extend the ideas of algorithm scalability and performance iso-efficiency to characterize the system-wide energy consumption. The latter includes dynamic and leakage energy for CPUs, memories and network interconnects. We propose analytical models for evaluating energy scalability and energy efficiency. These models are important for understanding the power consumption trends of data intensive applications executing on a large number of processors. We apply the models to two scientific applications to explore opportunities when using voltage/ frequency scaling for energy savings without degrading performance. Our results indicate that such models are critical for energy-aware high-performance computing in the tera- to peta-scale regime.

Original languageEnglish (US)
Title of host publicationIPDPS Miami 2008 - Proceedings of the 22nd IEEE International Parallel and Distributed Processing Symposium, Program and CD-ROM
DOIs
StatePublished - Sep 10 2008
EventIPDPS 2008 - 22nd IEEE International Parallel and Distributed Processing Symposium - Miami, FL, United States
Duration: Apr 14 2008Apr 18 2008

Publication series

NameIPDPS Miami 2008 - Proceedings of the 22nd IEEE International Parallel and Distributed Processing Symposium, Program and CD-ROM

Other

OtherIPDPS 2008 - 22nd IEEE International Parallel and Distributed Processing Symposium
CountryUnited States
CityMiami, FL
Period4/14/084/18/08

All Science Journal Classification (ASJC) codes

  • Hardware and Architecture
  • Software
  • Electrical and Electronic Engineering

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    Ding, Y., Malkowski, K., Raghavan, P., & Kandemir, M. (2008). Towards energy efficient scaling of scientific codes. In IPDPS Miami 2008 - Proceedings of the 22nd IEEE International Parallel and Distributed Processing Symposium, Program and CD-ROM [4536217] (IPDPS Miami 2008 - Proceedings of the 22nd IEEE International Parallel and Distributed Processing Symposium, Program and CD-ROM). https://doi.org/10.1109/IPDPS.2008.4536217