Energy Conservation Through Cloned Execution of Simulations

Srikanth B. Yoginath, Maksudul Alam, Kalyan S. Perumalla

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Scopus citations

Abstract

High-performance computing facilities used for scientific computing draw enormous energy, some of them consuming many megawatt-hours. Saving the energy consumption of computations on such facilities can dramatically reduce the total cost of their operation and help reduce environmental effects. Here, we focus on a way to reduce energy consumption in many ensembles of simulations. Using the method of simulation cloning to exploit parallelism while also significantly conserving the computational and memory requirements, we perform a detailed empirical study of energy consumed on a large supercomputer consisting of hardware accelerator cards (graphical processing units, GPUs). We build on previous insights from mathematical analysis and implementation of cloned simulations that result in computational and memory savings by several orders-of-magnitude. Using instrumentation to track the power drawn by thousands of accelerator cards, we report significant aggregate energy savings from cloned simulations.

Original languageEnglish
Title of host publication2019 Winter Simulation Conference, WSC 2019
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages2572-2582
Number of pages11
ISBN (Electronic)9781728132839
DOIs
StatePublished - Dec 2019
Event2019 Winter Simulation Conference, WSC 2019 - National Harbor, United States
Duration: Dec 8 2019Dec 11 2019

Publication series

NameProceedings - Winter Simulation Conference
Volume2019-December
ISSN (Print)0891-7736

Conference

Conference2019 Winter Simulation Conference, WSC 2019
Country/TerritoryUnited States
CityNational Harbor
Period12/8/1912/11/19

Funding

This manuscript has been authored by UT-Battelle, LLC under Contract No. DE-AC05-00OR22725 with the U.S. Department of Energy. The United States Government retains and the publisher, by accepting the article for publication, acknowledges that the United States Government retains a non-exclusive, paid-up, irrevocable, worldwide license to publish or reproduce the published form of this manuscript, or allow others to do so, for United States Government purposes. The Department of Energy will provide public access to these results of federally sponsored research in accordance with the DOE Public Access Plan. This research used resources of the Oak Ridge Leadership Computing Facility, which is a DOE Office of Science User Facility supported under Contract DE-AC05-00OR22725.

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