{"title":"Controlling Application Grain Size on a Network of Workstations","authors":"B. Siegell, P. Steenkiste","doi":"10.1145/224170.224497","DOIUrl":null,"url":null,"abstract":"An important challenge in the area of distributed computing is to automate the selection of the parameters that control the distributed computation. A performance-critical parameter is the grain size of the computation, i.e., the interval between successive synchronization points in the application. This parameter is hard to select since it depends both on compile time (loop structure and data dependences, computational complexity) and run time components (speed of compute nodes and network). On networks of workstations that are shared with other users, the run-time parameters can change over time. As a result, it is also necessary to consider the interactions with dynamic load balancing, which is needed to achieve good performance in this environment. In this paper we present a method for automatically selecting the grain size of the computation consisting of nested DO loops. The method is based on close cooperation between the compiler and the runtime system. We evaluate the method using both simulation and measurements for an implementation on the Nectar multicomputer.","PeriodicalId":269909,"journal":{"name":"Proceedings of the IEEE/ACM SC95 Conference","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1995-12-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"7","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the IEEE/ACM SC95 Conference","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/224170.224497","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 7
Abstract
An important challenge in the area of distributed computing is to automate the selection of the parameters that control the distributed computation. A performance-critical parameter is the grain size of the computation, i.e., the interval between successive synchronization points in the application. This parameter is hard to select since it depends both on compile time (loop structure and data dependences, computational complexity) and run time components (speed of compute nodes and network). On networks of workstations that are shared with other users, the run-time parameters can change over time. As a result, it is also necessary to consider the interactions with dynamic load balancing, which is needed to achieve good performance in this environment. In this paper we present a method for automatically selecting the grain size of the computation consisting of nested DO loops. The method is based on close cooperation between the compiler and the runtime system. We evaluate the method using both simulation and measurements for an implementation on the Nectar multicomputer.