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DTSTART:19700308T020000
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DTSTAMP:20260522T150120Z
LOCATION:C141/143/149
DTSTART;TZID=America/Chicago:20181115T153000
DTEND;TZID=America/Chicago:20181115T160000
UID:submissions.supercomputing.org_SC18_sess186_pap407@linklings.com
SUMMARY:Dac-Man: Data Change Management for Scientific Datasets on HPC Sys
 tems
DESCRIPTION:Devarshi Ghoshal, Lavanya Ramakrishnan, and Deborah Agarwal (L
 awrence Berkeley National Laboratory)\n\nScientific data is growing rapidl
 y and often changes due to instrument configurations, software updates, or
  quality assessments. These changes in datasets can result in significant 
 waste of compute and storage resources on HPC systems as downstream pipeli
 nes are reprocessed. Data changes need to be detected, tracked, and analyz
 ed for understanding the impact of data change, managing data provenance, 
 and making efficient and effective decisions about reprocessing and use of
  HPC resources. Existing methods for identifying and capturing change are 
 often manual, domain-specific, and error-prone and do not scale to large s
 cientific datasets. In this paper, we describe the design and implementati
 on of Dac-Man framework, which identifies, captures, and manages change in
  large scientific datasets, and enables plug-in of domain-specific change 
 analysis with minimal user effort. Our evaluations show that it can retrie
 ve file changes from directories containing millions of files and terabyte
 s of data in less than a minute.\n\nTag: Architectures, Data Management, F
 ile Systems, Networks, State of the Practice, System Software, Workflows\n
 \nRegistration Category: Tech Program Reg Pass\n\nSession Chair: Robin J. 
 Goldstone (Lawrence Livermore National Laboratory)\n\n
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