{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,19]],"date-time":"2025-03-19T16:59:07Z","timestamp":1742403547064},"reference-count":3,"publisher":"World Scientific Pub Co Pte Lt","issue":"04","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Parallel Process. Lett."],"published-print":{"date-parts":[[2005,12]]},"abstract":"<jats:p> In this paper we describe an important use of predictive application performance modeling - the validation of measured performance during a new large-scale system installation. Using a previously-developed and validated performance model for SAGE, a multidimensional, 3D, multi-material hydrodynamics code with adaptive mesh refinement, we were able to help guide the stabilization of the first phase of the Los Alamos ASCI Q supercomputer. We review the salient features of an analytical model for this code that has been applied to predict its performance on a large class of Tera-scale parallel systems. We describe the methodology applied during system installation and upgrades to establish a baseline for the achievable \"real\" performance of the system. We also show the effect on overall application performance of certain key subsystems such as PCI bus speed and multi-rail networks. We show that utilization of predictive performance models is also a powerful system debugging tool. <\/jats:p>","DOI":"10.1142\/s0129626405002301","type":"journal-article","created":{"date-parts":[[2006,1,3]],"date-time":"2006-01-03T11:55:56Z","timestamp":1136289356000},"page":"387-395","source":"Crossref","is-referenced-by-count":14,"title":["USE OF PREDICTIVE PERFORMANCE MODELING DURING LARGE-SCALE SYSTEM INSTALLATION"],"prefix":"10.1142","volume":"15","author":[{"given":"DARREN J.","family":"KERBYSON","sequence":"first","affiliation":[{"name":"Performance and Architectures Laboratory, Modeling, Algorithms and Informatics Group, CCS-3, Los Alamos National Laboratory, Los Alamos, NM 87545, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"ADOLFY","family":"HOISIE","sequence":"additional","affiliation":[{"name":"Performance and Architectures Laboratory, Modeling, Algorithms and Informatics Group, CCS-3, Los Alamos National Laboratory, Los Alamos, NM 87545, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"HARVEY J.","family":"WASSERMAN","sequence":"additional","affiliation":[{"name":"Performance and Architectures Laboratory, Modeling, Algorithms and Informatics Group, CCS-3, Los Alamos National Laboratory, Los Alamos, NM 87545, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"219","published-online":{"date-parts":[[2011,11,21]]},"reference":[{"key":"rf2","doi-asserted-by":"publisher","DOI":"10.1177\/109434200001400405"},{"key":"rf3","doi-asserted-by":"publisher","DOI":"10.1109\/40.988689"},{"key":"rf7","volume-title":"Performance Analysis and Grid Computing","author":"Kerbyson D. J.","year":"2003"}],"container-title":["Parallel Processing Letters"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.worldscientific.com\/doi\/pdf\/10.1142\/S0129626405002301","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2019,8,7]],"date-time":"2019-08-07T13:29:13Z","timestamp":1565184553000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.worldscientific.com\/doi\/abs\/10.1142\/S0129626405002301"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2005,12]]},"references-count":3,"journal-issue":{"issue":"04","published-online":{"date-parts":[[2011,11,21]]},"published-print":{"date-parts":[[2005,12]]}},"alternative-id":["10.1142\/S0129626405002301"],"URL":"https:\/\/doi.org\/10.1142\/s0129626405002301","relation":{},"ISSN":["0129-6264","1793-642X"],"issn-type":[{"value":"0129-6264","type":"print"},{"value":"1793-642X","type":"electronic"}],"subject":[],"published":{"date-parts":[[2005,12]]}}}