{"title":"Data parallel fault simulation","authors":"M. Amin, B. Vinnakota","doi":"10.1109/ICCD.1995.528931","DOIUrl":null,"url":null,"abstract":"Fault simulation is a compute intensive problem. Data parallel simulation on multiple processors is one method to reduce fault simulation time. We discuss a novel technique to partition the fault set for data parallel fault simulation. When applied statically, the technique can scale well for up to eight processors. The fault set partitioning technique is simple, can itself be parallelized, and can be implemented with extreme ease. Therefore, the technique can be used on a low cost parallel resource, such as a network of workstations.","PeriodicalId":281907,"journal":{"name":"Proceedings of ICCD '95 International Conference on Computer Design. VLSI in Computers and Processors","volume":"10 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1995-10-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"31","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of ICCD '95 International Conference on Computer Design. VLSI in Computers and Processors","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCD.1995.528931","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 31

Abstract

Fault simulation is a compute intensive problem. Data parallel simulation on multiple processors is one method to reduce fault simulation time. We discuss a novel technique to partition the fault set for data parallel fault simulation. When applied statically, the technique can scale well for up to eight processors. The fault set partitioning technique is simple, can itself be parallelized, and can be implemented with extreme ease. Therefore, the technique can be used on a low cost parallel resource, such as a network of workstations.
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数据并行故障模拟
故障仿真是一个计算密集型问题。多处理器数据并行仿真是减少故障仿真时间的一种方法。讨论了一种数据并行故障模拟中故障集划分的新方法。当静态应用时,该技术可以很好地扩展到最多八个处理器。故障集分区技术很简单,本身可以并行化,并且可以非常容易地实现。因此,该技术可用于低成本的并行资源,如工作站网络。
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