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DTSTART:19700308T020000
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DTSTAMP:20200129T163557Z
LOCATION:708
DTSTART;TZID=America/Denver:20191117T113000
DTEND;TZID=America/Denver:20191117T120000
UID:submissions.supercomputing.org_SC19_sess112_pec242@linklings.com
SUMMARY:Top-Down Performance Analysis Methodology for Workflows: Tracking 
 Performance Issues from Overview to Individual Operations
DESCRIPTION:Workshop\n\nTop-Down Performance Analysis Methodology for Work
 flows: Tracking Performance Issues from Overview to Individual Operations\
 n\nTschueter, Herold, Williams, Knespel, Weber\n\nScientific workflows are
  well established in parallel computing. A workflow represents a conceptua
 l description of work items and their dependencies. Researchers can use wo
 rkflows to abstract away implementation details or resources to focus on t
 he high-level behavior of their work items. Due to these abstractions and 
 the complexity of scientific workflows, finding performance bottlenecks al
 ong with their root causes can quickly become involving. This work present
 s a top-down methodology for performance analysis of workflows to support 
 users in this challenging task. Our work provides summarized performance m
 etrics covering different workflow perspectives, from general overview to 
 individual jobs and their job steps. These summaries allow to identify ine
 fficiencies and determine the responsible job steps. In addition, we recor
 d detailed performance data about job steps, enabling a fine-grained analy
 sis of the associated execution to exactly pinpoint performance issues. Th
 e introduced methodology provides a powerful tool for comprehensive perfor
 mance analysis of complex workflows.\n\nTag: Workshop Reg Pass, Extreme Sc
 ale Computing, Scalable Computing, Scientific Workflows\n\nRegistration Ca
 tegory: Workshop Reg Pass, Extreme Scale Computing, Scalable Computing, Sc
 ientific Workflows
URL:https://sc19.supercomputing.org/presentation/?id=pec242&sess=sess112
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