Owen Mylotte, Matthew T. McGurn, Kenneth Budzinski, Paul E. DesJardin
{"title":"Ray decomposition radiation transport for high performance computing","authors":"Owen Mylotte, Matthew T. McGurn, Kenneth Budzinski, Paul E. DesJardin","doi":"10.1016/j.jcp.2024.113567","DOIUrl":null,"url":null,"abstract":"<div><div>Radiation transport is essential in many high-performance computing problems. However, its complexity presents computational challenges. This study presents a novel algorithm, the ray decomposition method for long characteristics transport, designed to address communication challenges specific to distributed memory computing. Reordering of ray property calculations reduces communication cost associated with sequential ray integration. Verification studies demonstrate solution convergence. Performance modeling of the ray decomposition method predicts the compute time from first principles. Consistency of experimentally measured performance with analytical predictions validates the performance scaling model. This work represents a step towards more scalable and efficient radiation transport simulations.</div></div>","PeriodicalId":352,"journal":{"name":"Journal of Computational Physics","volume":"521 ","pages":"Article 113567"},"PeriodicalIF":3.8000,"publicationDate":"2024-11-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Computational Physics","FirstCategoryId":"101","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0021999124008155","RegionNum":2,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS","Score":null,"Total":0}
引用次数: 0
Abstract
Radiation transport is essential in many high-performance computing problems. However, its complexity presents computational challenges. This study presents a novel algorithm, the ray decomposition method for long characteristics transport, designed to address communication challenges specific to distributed memory computing. Reordering of ray property calculations reduces communication cost associated with sequential ray integration. Verification studies demonstrate solution convergence. Performance modeling of the ray decomposition method predicts the compute time from first principles. Consistency of experimentally measured performance with analytical predictions validates the performance scaling model. This work represents a step towards more scalable and efficient radiation transport simulations.
期刊介绍:
Journal of Computational Physics thoroughly treats the computational aspects of physical problems, presenting techniques for the numerical solution of mathematical equations arising in all areas of physics. The journal seeks to emphasize methods that cross disciplinary boundaries.
The Journal of Computational Physics also publishes short notes of 4 pages or less (including figures, tables, and references but excluding title pages). Letters to the Editor commenting on articles already published in this Journal will also be considered. Neither notes nor letters should have an abstract.