{"title":"消息传递程序的自动建模","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":"{\"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}","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}
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.<>