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LOCATION:Track 1
DTSTART;TZID=America/New_York:20201112T112000
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UID:submissions.supercomputing.org_SC20_sess207_ws_drbsd102@linklings.com
SUMMARY:Toward a Framework for Policy-Driven Adaptive In Situ Workflows
DESCRIPTION:Workshop\n\nToward a Framework for Policy-Driven Adaptive In S
 itu Workflows\n\nMehta, Singhal, Wolf, Podhorszki, Logan...\n\nAs we move 
 toward exascale, managing vast volumes of data and extracting knowledge fr
 om it in a timely way has become a challenge for science. In situ analysis
  of data is a viable alternative to processing large data volumes post-hoc
 . However, composing and orchestrating in situ workflows remains challengi
 ng due to variability in the system behavior at runtime and the need to ad
 dress dynamically occurring events in the science application. Thus, dynam
 ic control of a running workflow is an important step for the next generat
 ion of high performance computing.\n\nThis paper presents initial work tow
 ards a policy-driven framework for dynamically controllable in situ workfl
 ows.  We present example policies that can be used to dynamically tune a r
 unning workflow, and show that to enact these policies, a framework will n
 eed to provide support in both the data management library and the workflo
 w tools layer. We present a keyword-based specification to express simple 
 policies.  Through experiments on Summit, a pre-exascale supercomputer at 
 Oak Ridge National Laboratory, we demonstrate the impact of a dynamically 
 adaptive HPC workflow.\n\nRegistration Category: Workshop Reg Pass
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