{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2022,4,1]],"date-time":"2022-04-01T00:01:47Z","timestamp":1648771307218},"reference-count":5,"publisher":"World Scientific Pub Co Pte Lt","issue":"03","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Parallel Process. Lett."],"published-print":{"date-parts":[[2011,9]]},"abstract":"<jats:p> Direct Numerical Simulation (DNS) is an important application area that is expected to use large fractions of future large-scale simulations. In this work we develop, validate and use a performance model of the combustion code, DNS3D, to explore achieved performance on current parallel systems. The performance model is developed from a thorough analysis of the application. Its key computation characteristics are coupled with the performance characteristics of the system using an parameterized analytical model. The model is validated on three parallel systems: a muti-core AMD Opteron based system with an Infiniband fat-tree network, an IBM Power5+ system with an HPS fat-tree network, and an IBM Power7 system with a direct connect network. The performance model is shown to achieve high prediction accuracy on all three systems. We illustrate how the model can be used to explore impact of changes in either the system or the application. It is used to both analyze the achieved performance on these systems as well as to explore the possible benefits of further optimizing DNS3D's main computational kernel of one-dimensional FFTs, or in possibly overlapping communication with computation. <\/jats:p>","DOI":"10.1142\/s0129626411000230","type":"journal-article","created":{"date-parts":[[2011,9,14]],"date-time":"2011-09-14T06:52:32Z","timestamp":1315983152000},"page":"301-318","source":"Crossref","is-referenced-by-count":0,"title":["MODELING THE PERFORMANCE OF DIRECT NUMERICAL SIMULATION ON PARALLEL SYSTEMS"],"prefix":"10.1142","volume":"21","author":[{"given":"DARREN J.","family":"KERBYSON","sequence":"first","affiliation":[{"name":"Performance and Architecture Lab (PAL), Pacific Northwest National Laboratory, Richland, WA 99353, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"KEVIN J.","family":"BARKER","sequence":"additional","affiliation":[{"name":"Performance and Architecture Lab (PAL), Pacific Northwest National Laboratory, Richland, WA 99353, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"219","published-online":{"date-parts":[[2011,11,21]]},"reference":[{"key":"rf1","volume":"4","author":"Jimenez J.","journal-title":"J. Turbulence"},{"key":"rf4","first-page":"142","volume":"29","author":"Kurien S.","journal-title":"Los Alamos Science"},{"key":"rf5","doi-asserted-by":"publisher","DOI":"10.1109\/MC.2009.372"},{"key":"rf7","doi-asserted-by":"publisher","DOI":"10.1177\/109434200001400405"},{"key":"rf8","doi-asserted-by":"publisher","DOI":"10.1177\/1094342005056114"}],"container-title":["Parallel Processing Letters"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.worldscientific.com\/doi\/pdf\/10.1142\/S0129626411000230","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2019,8,6]],"date-time":"2019-08-06T12:17:13Z","timestamp":1565093833000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.worldscientific.com\/doi\/abs\/10.1142\/S0129626411000230"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2011,9]]},"references-count":5,"journal-issue":{"issue":"03","published-online":{"date-parts":[[2011,11,21]]},"published-print":{"date-parts":[[2011,9]]}},"alternative-id":["10.1142\/S0129626411000230"],"URL":"https:\/\/doi.org\/10.1142\/s0129626411000230","relation":{},"ISSN":["0129-6264","1793-642X"],"issn-type":[{"value":"0129-6264","type":"print"},{"value":"1793-642X","type":"electronic"}],"subject":[],"published":{"date-parts":[[2011,9]]}}}