{"title":"Directive-Based Parallelization of the NIM Weather Model for GPUs","authors":"M. Govett, J. Middlecoff, T. Henderson","doi":"10.1109/WACCPD.2014.9","DOIUrl":null,"url":null,"abstract":"The NIM is a performance-portable model that runs on CPU, GPU and MIC architectures with a single source code. The single source plus efficient code design allows application scientists to maintain the Fortran code, while computer scientists optimize performance and portability using OpenMP, OpenACC, and F2CACC directives. The F2C-ACC compiler was developed in 2008 at NOAA's Earth System Research Laboratory (ESRL) to support GPU parallelization before commercial Fortran GPU compilers were available. Since then, a number of vendors have built GPU compilers that are compliant to the emerging OpenACC standard. The paper will compare parallelization and performance of NIM using the F2C-ACC, Cray and PGI Fortran GPU compilers.","PeriodicalId":179664,"journal":{"name":"2014 First Workshop on Accelerator Programming using Directives","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2014-11-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"22","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2014 First Workshop on Accelerator Programming using Directives","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/WACCPD.2014.9","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 22
Abstract
The NIM is a performance-portable model that runs on CPU, GPU and MIC architectures with a single source code. The single source plus efficient code design allows application scientists to maintain the Fortran code, while computer scientists optimize performance and portability using OpenMP, OpenACC, and F2CACC directives. The F2C-ACC compiler was developed in 2008 at NOAA's Earth System Research Laboratory (ESRL) to support GPU parallelization before commercial Fortran GPU compilers were available. Since then, a number of vendors have built GPU compilers that are compliant to the emerging OpenACC standard. The paper will compare parallelization and performance of NIM using the F2C-ACC, Cray and PGI Fortran GPU compilers.