Akademska digitalna zbirka SLovenije - logo
E-resources
Full text
Peer reviewed Open access
  • The Exascale Framework for ...
    Suchyta, Eric; Klasky, Scott; Podhorszki, Norbert; Wolf, Matthew; Adesoji, Abolaji; Chang, CS; Choi, Jong; Davis, Philip E; Dominski, Julien; Ethier, Stéphane; Foster, Ian; Germaschewski, Kai; Geveci, Berk; Harris, Chris; Huck, Kevin A; Liu, Qing; Logan, Jeremy; Mehta, Kshitij; Merlo, Gabriele; Moore, Shirley V; Munson, Todd; Parashar, Manish; Pugmire, David; Shephard, Mark S; Smith, Cameron W; Subedi, Pradeep; Wan, Lipeng; Wang, Ruonan; Zhang, Shuangxi

    The international journal of high performance computing applications, 01/2022, Volume: 36, Issue: 1
    Journal Article

    We present the Exascale Framework for High Fidelity coupled Simulations (EFFIS), a workflow and code coupling framework developed as part of the Whole Device Modeling Application (WDMApp) in the Exascale Computing Project. EFFIS consists of a library, command line utilities, and a collection of run-time daemons. Together, these software products enable users to easily compose and execute workflows that include: strong or weak coupling, in situ (or offline) analysis/visualization/monitoring, command-and-control actions, remote dashboard integration, and more. We describe WDMApp physics coupling cases and computer science requirements that motivate the design of the EFFIS framework. Furthermore, we explain the essential enabling technology that EFFIS leverages: ADIOS for performant data movement, PerfStubs/TAU for performance monitoring, and an advanced COUPLER for transforming coupling data from its native format to the representation needed by another application. Finally, we demonstrate EFFIS using coupled multi-simulation WDMApp workflows and exemplify how the framework supports the project’s needs. We show that EFFIS and its associated services for data movement, visualization, and performance collection does not introduce appreciable overhead to the WDMApp workflow and that the resource-dominant application’s idle time while waiting for data is minimal.