{"title":"预测MPI应用程序的行为","authors":"Marc Casas, Rosa M. Badia, Jesús Labarta","doi":"10.1109/CLUSTR.2008.4663777","DOIUrl":null,"url":null,"abstract":"Scalability and performance of applications is a very important issue today. As more complex have become high performance architectures, it is more complex to predict the behavior of a given application running on them. In this paper, we propose a methodology which automatically and quickly predicts, from a very limited number of runs using very few processors, the scalability and performance of a given application in a wide range of supercomputers taking into account details of the architecture and the network of the machines.","PeriodicalId":198768,"journal":{"name":"2008 IEEE International Conference on Cluster Computing","volume":"5 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2008-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"8","resultStr":"{\"title\":\"Prediction of behavior of MPI applications\",\"authors\":\"Marc Casas, Rosa M. Badia, Jesús Labarta\",\"doi\":\"10.1109/CLUSTR.2008.4663777\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Scalability and performance of applications is a very important issue today. As more complex have become high performance architectures, it is more complex to predict the behavior of a given application running on them. In this paper, we propose a methodology which automatically and quickly predicts, from a very limited number of runs using very few processors, the scalability and performance of a given application in a wide range of supercomputers taking into account details of the architecture and the network of the machines.\",\"PeriodicalId\":198768,\"journal\":{\"name\":\"2008 IEEE International Conference on Cluster Computing\",\"volume\":\"5 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2008-10-31\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"8\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2008 IEEE International Conference on Cluster Computing\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CLUSTR.2008.4663777\",\"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.2008.4663777","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Scalability and performance of applications is a very important issue today. As more complex have become high performance architectures, it is more complex to predict the behavior of a given application running on them. In this paper, we propose a methodology which automatically and quickly predicts, from a very limited number of runs using very few processors, the scalability and performance of a given application in a wide range of supercomputers taking into account details of the architecture and the network of the machines.
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