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DTSTAMP:20211207T055402Z
LOCATION:Online
DTSTART;TZID=America/Chicago:20211115T142500
DTEND;TZID=America/Chicago:20211115T145000
UID:submissions.supercomputing.org_SC21_sess342_ws_worksp107@linklings.com
SUMMARY:An Adaptive Elasticity Policy For Staging Based In-Situ Processing
DESCRIPTION:Workshop\n\nAn Adaptive Elasticity Policy For Staging Based In
 -Situ Processing\n\nWang, Dorier, Subedi, E. Davis, Parashar\n\nIn-situ pr
 ocessing alleviates the gap between computation and I/O capabilities by pe
 rforming data analysis close to the data source. With simulation data vary
 ing in size and content during workflow execution, it becomes necessary fo
 r in-situ processing to support resource elasticity, i.e., the ability to 
 change resource configurations such as the number of computing nodes/proce
 sses during workflow execution. An elastic job may dynamically adjust reso
 urce configurations; it may use a few resources at the beginning but uses 
 more resources towards the end of the job when interesting data appears. H
 owever, it is hard to predict a priori how many computing nodes/processes 
 need to be added/removed during the workflow execution to adapt to changin
 g workflow needs. How to efficiently guide elasticity operations, such as 
 growing or shrinking process quantity used for in-situ processing during w
 orkflow execution, is an open-ended research question. In this paper, we p
 resent an adaptive elasticity policy that adopts workflow runtime informat
 ion collected online to predict how to trigger the addition and removal of
  processes in order to minimize in-situ processing overheads. We integrate
  the presented elasticity policy into a staging-based elastic workflow and
  evaluate its efficiency in multiple elasticity scenarios. The results ind
 icate that an adaptive elasticity policy can save overhead in finding a pr
 oper resource configuration when compared with a static policy that uses a
  fixed number of processes for each rescaling operation. Finally, we discu
 ss multiple existing research opportunities of elastic in-situ processing 
 from different aspects.\n\nTag: Online Only, Cloud and Distributed Computi
 ng, Scientific Computing, Workflows\n\nRegistration Category: Workshop Reg
  Pass
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