{"title":"分布式离散事件仿真的文献综述","authors":"F. Kaudel","doi":"10.1145/29497.29499","DOIUrl":null,"url":null,"abstract":"Much literature over the past decade has examined using multiprocessors to increase the speed and lower the cost of discrete event simulation. Three orthogonal approaches have been suggested, using simulation parallelism in support functions, in model functions and on the application level. This overview brings together these past approaches into a new framework wherein all three can be used simultaneously and suggests several promising research areas.","PeriodicalId":138785,"journal":{"name":"ACM Sigsim Simulation Digest","volume":"6 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1987-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"46","resultStr":"{\"title\":\"A literature survey on distributed discrete event simulation\",\"authors\":\"F. Kaudel\",\"doi\":\"10.1145/29497.29499\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Much literature over the past decade has examined using multiprocessors to increase the speed and lower the cost of discrete event simulation. Three orthogonal approaches have been suggested, using simulation parallelism in support functions, in model functions and on the application level. This overview brings together these past approaches into a new framework wherein all three can be used simultaneously and suggests several promising research areas.\",\"PeriodicalId\":138785,\"journal\":{\"name\":\"ACM Sigsim Simulation Digest\",\"volume\":\"6 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1987-06-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"46\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"ACM Sigsim Simulation Digest\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/29497.29499\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"ACM Sigsim Simulation Digest","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/29497.29499","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A literature survey on distributed discrete event simulation
Much literature over the past decade has examined using multiprocessors to increase the speed and lower the cost of discrete event simulation. Three orthogonal approaches have been suggested, using simulation parallelism in support functions, in model functions and on the application level. This overview brings together these past approaches into a new framework wherein all three can be used simultaneously and suggests several promising research areas.