{"title":"使用EC/DSIM分析内存和时间节省","authors":"Gudjon Hermannsson, Ai Li, L. Wittie","doi":"10.1109/MASCOT.1994.284421","DOIUrl":null,"url":null,"abstract":"This paper introduces the EC frontend and DSIM simulator. Given a parallel program, they determine its execution time on huge networks of computers. EC extracts task step needs. DSIM predicts completion times rather than simulating each program step. This paper contains analyses of the memory savings and the execution time savings for simulations of one to 2,800 computers running parallel Gaussian elimination and fast Fourier transform. The time savings are 20% (two days) for fifty runs of Gaussian reduction of a 400x401 matrix to solve 400 linear equations. Memory needs are reduced 99% (637 MBytes) per simulation run. The memory savings allow simulation of parallel programs running on thousands of processors. These huge network sizes are impractical with step-by-step simulations.<<ETX>>","PeriodicalId":288344,"journal":{"name":"Proceedings of International Workshop on Modeling, Analysis and Simulation of Computer and Telecommunication Systems","volume":"80 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1994-01-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Analysis of memory and time savings using EC/DSIM\",\"authors\":\"Gudjon Hermannsson, Ai Li, L. Wittie\",\"doi\":\"10.1109/MASCOT.1994.284421\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper introduces the EC frontend and DSIM simulator. Given a parallel program, they determine its execution time on huge networks of computers. EC extracts task step needs. DSIM predicts completion times rather than simulating each program step. This paper contains analyses of the memory savings and the execution time savings for simulations of one to 2,800 computers running parallel Gaussian elimination and fast Fourier transform. The time savings are 20% (two days) for fifty runs of Gaussian reduction of a 400x401 matrix to solve 400 linear equations. Memory needs are reduced 99% (637 MBytes) per simulation run. The memory savings allow simulation of parallel programs running on thousands of processors. These huge network sizes are impractical with step-by-step simulations.<<ETX>>\",\"PeriodicalId\":288344,\"journal\":{\"name\":\"Proceedings of International Workshop on Modeling, Analysis and Simulation of Computer and Telecommunication Systems\",\"volume\":\"80 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1994-01-31\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"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.1994.284421\",\"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.1994.284421","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
This paper introduces the EC frontend and DSIM simulator. Given a parallel program, they determine its execution time on huge networks of computers. EC extracts task step needs. DSIM predicts completion times rather than simulating each program step. This paper contains analyses of the memory savings and the execution time savings for simulations of one to 2,800 computers running parallel Gaussian elimination and fast Fourier transform. The time savings are 20% (two days) for fifty runs of Gaussian reduction of a 400x401 matrix to solve 400 linear equations. Memory needs are reduced 99% (637 MBytes) per simulation run. The memory savings allow simulation of parallel programs running on thousands of processors. These huge network sizes are impractical with step-by-step simulations.<>
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