{"title":"Automated modeling of message-passing programs","authors":"P. Mehra, M. Gower, Michael A. Bass","doi":"10.1109/MASCOT.1994.284424","DOIUrl":null,"url":null,"abstract":"We present a system for automated modeling of message-passing programs. Its models preserve the parallel program's structure, especially the syntactic boundaries surrounding communication calls. Our grammar-driven approach uses the program's parse trees to derive a regular expression that describes all possible execution traces at the chosen level of modeling; that expression is used for automatic extraction of timing information from traces of scaled-down runs. We consider \"intelligent regression\" techniques for discovering the numerical attributes of our models: run times of sequential blocks; lengths and destinations of messages; and loop bounds. Regression produces formulae expressing these attributes in terms of problem and system sizes. The model is then used for predicting the performance of large-scale runs. We illustrate our approach with a program that simultaneously solves multiple tridiagonal linear systems an the iPSC/860.<<ETX>>","PeriodicalId":288344,"journal":{"name":"Proceedings of International Workshop on Modeling, Analysis and Simulation of Computer and Telecommunication Systems","volume":"9 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1994-01-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"15","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of International Workshop on Modeling, Analysis and Simulation of Computer and Telecommunication Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/MASCOT.1994.284424","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 15
Abstract
We present a system for automated modeling of message-passing programs. Its models preserve the parallel program's structure, especially the syntactic boundaries surrounding communication calls. Our grammar-driven approach uses the program's parse trees to derive a regular expression that describes all possible execution traces at the chosen level of modeling; that expression is used for automatic extraction of timing information from traces of scaled-down runs. We consider "intelligent regression" techniques for discovering the numerical attributes of our models: run times of sequential blocks; lengths and destinations of messages; and loop bounds. Regression produces formulae expressing these attributes in terms of problem and system sizes. The model is then used for predicting the performance of large-scale runs. We illustrate our approach with a program that simultaneously solves multiple tridiagonal linear systems an the iPSC/860.<>