{"title":"以openmp为中心的混合应用程序性能分析","authors":"K. Fürlinger, S. Moore","doi":"10.1109/CLUSTR.2008.4663767","DOIUrl":null,"url":null,"abstract":"Several performance analysis tools support hybrid applications. Most originated as MPI profiling or tracing tools and OpenMP capabilities were added to extend the performance analysis capabilities for the hybrid parallelization case. In this paper we describe our experience with the other path to support both programming paradigms. Our starting point is a profiling tool for OpenMP called ompP that was extended to handle MPI related data. The measured data and the method of presentation follow our focus on the OpenMP side of the performance optimization cycle. For example, the existing overhead classification scheme of ompP was extended to cover time in MPI calls as a new type of overhead.","PeriodicalId":198768,"journal":{"name":"2008 IEEE International Conference on Cluster Computing","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2008-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"OpenMP-centric performance analysis of hybrid applications\",\"authors\":\"K. Fürlinger, S. Moore\",\"doi\":\"10.1109/CLUSTR.2008.4663767\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Several performance analysis tools support hybrid applications. Most originated as MPI profiling or tracing tools and OpenMP capabilities were added to extend the performance analysis capabilities for the hybrid parallelization case. In this paper we describe our experience with the other path to support both programming paradigms. Our starting point is a profiling tool for OpenMP called ompP that was extended to handle MPI related data. The measured data and the method of presentation follow our focus on the OpenMP side of the performance optimization cycle. For example, the existing overhead classification scheme of ompP was extended to cover time in MPI calls as a new type of overhead.\",\"PeriodicalId\":198768,\"journal\":{\"name\":\"2008 IEEE International Conference on Cluster Computing\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2008-10-31\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2008 IEEE International Conference on Cluster Computing\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CLUSTR.2008.4663767\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2008 IEEE International Conference on Cluster Computing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CLUSTR.2008.4663767","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
OpenMP-centric performance analysis of hybrid applications
Several performance analysis tools support hybrid applications. Most originated as MPI profiling or tracing tools and OpenMP capabilities were added to extend the performance analysis capabilities for the hybrid parallelization case. In this paper we describe our experience with the other path to support both programming paradigms. Our starting point is a profiling tool for OpenMP called ompP that was extended to handle MPI related data. The measured data and the method of presentation follow our focus on the OpenMP side of the performance optimization cycle. For example, the existing overhead classification scheme of ompP was extended to cover time in MPI calls as a new type of overhead.
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