{"title":"Fine-Grained Profiling for Data-Intensive Workflows","authors":"N. Dun, K. Taura, A. Yonezawa","doi":"10.1109/CCGRID.2010.29","DOIUrl":null,"url":null,"abstract":"Profiling is an effective dynamic analysis approach to investigate complex applications. ParaTrac is a user-level profiler using file system and process tracing techniques for data-intensive workflow applications. In two respects ParaTrac helps users refine the orchestration of workflows. First, the profiles of I/O characteristics enable users to quickly identify bottlenecks of underlying I/O subsystems. Second, ParaTrac can exploit fine-grained data-processes interactions in workflow execution to help users understand, characterize, and manage realistic data-intensive workflows. Experiments on thoroughly profiling Montage workflow demonstrate that ParaTrac is scalable to tracing events of thousands of processes and effective in guiding fine-grained workflow scheduling or workflow management systems improvements.","PeriodicalId":444485,"journal":{"name":"2010 10th IEEE/ACM International Conference on Cluster, Cloud and Grid Computing","volume":"38 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2010-05-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2010 10th IEEE/ACM International Conference on Cluster, Cloud and Grid Computing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CCGRID.2010.29","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2
Abstract
Profiling is an effective dynamic analysis approach to investigate complex applications. ParaTrac is a user-level profiler using file system and process tracing techniques for data-intensive workflow applications. In two respects ParaTrac helps users refine the orchestration of workflows. First, the profiles of I/O characteristics enable users to quickly identify bottlenecks of underlying I/O subsystems. Second, ParaTrac can exploit fine-grained data-processes interactions in workflow execution to help users understand, characterize, and manage realistic data-intensive workflows. Experiments on thoroughly profiling Montage workflow demonstrate that ParaTrac is scalable to tracing events of thousands of processes and effective in guiding fine-grained workflow scheduling or workflow management systems improvements.