BEGIN:VCALENDAR
PRODID:-//Microsoft Corporation//Outlook MIMEDIR//EN
VERSION:1.0
BEGIN:VEVENT
DTSTART:20151119T170000Z
DTEND:20151119T173000Z
LOCATION:19AB
DESCRIPTION;ENCODING=QUOTED-PRINTABLE:ABSTRACT: Data staging and  in-situ/in-transit data processing are emerging as attractive approaches for supporting extreme scale scientific workflows. These approaches accelerate the data-to-insight process by enabling runtime data sharing between coupled simulations and data analytics components of the workflow. However, the complex and dynamic data exchange patterns exhibited by the workflows coupled with various data access behaviors make efficient data placement within the staging area challenging.  In this paper, we present an adaptive data placement approach to address these challenges. Our approach adapts data placement based on application-specific dynamic data access patterns, and applies access pattern-driven and location-aware mechanisms to reduce data access costs and to support efficient data sharing between multiple workflow components. We experimentally demonstrate the effectiveness of our approach on Titan using combustion-analyses workflow. The evaluation results show that our approach can effectively improve data access performance and the overall efficiency of coupled scientific workflows.
SUMMARY:Adaptive Data Placement for Staging-Based Coupled Scientific Workflows
PRIORITY:3
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END:VCALENDAR