{"title":"Trace Driven Data Structure Transformations","authors":"T. Janjusic, K. Kavi, Christos Kartsaklis","doi":"10.1109/SC.Companion.2012.65","DOIUrl":null,"url":null,"abstract":"As the complexity of scientific codes and computational hardware increases it is increasingly important to study the effects of data-structure layouts on program memory behavior. Program structure layouts affect the memory performance differently, therefore we need the capability to effectively study such transformations without the need to rewrite application codes. Trace-driven simulations are an effective and convenient mechanism to simulate program behavior at various granularities. During an application's execution, a tool known as a tracer or profiler, collects program flow data and records program instructions. The trace-file consists of tuples that associate each program instruction with program internal variables. In this paper we outline a proof-of-concept mechanism to apply data-structure transformations during trace simulation and observe effects on memory without the need to manually transform an application's code.","PeriodicalId":6346,"journal":{"name":"2012 SC Companion: High Performance Computing, Networking Storage and Analysis","volume":"146 1","pages":"456-464"},"PeriodicalIF":0.0000,"publicationDate":"2012-11-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2012 SC Companion: High Performance Computing, Networking Storage and Analysis","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SC.Companion.2012.65","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 4
Abstract
As the complexity of scientific codes and computational hardware increases it is increasingly important to study the effects of data-structure layouts on program memory behavior. Program structure layouts affect the memory performance differently, therefore we need the capability to effectively study such transformations without the need to rewrite application codes. Trace-driven simulations are an effective and convenient mechanism to simulate program behavior at various granularities. During an application's execution, a tool known as a tracer or profiler, collects program flow data and records program instructions. The trace-file consists of tuples that associate each program instruction with program internal variables. In this paper we outline a proof-of-concept mechanism to apply data-structure transformations during trace simulation and observe effects on memory without the need to manually transform an application's code.