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DTSTART:19700308T020000
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DTSTAMP:20211207T054813Z
LOCATION:240-241-242
DTSTART;TZID=America/Chicago:20211118T153000
DTEND;TZID=America/Chicago:20211118T160000
UID:submissions.supercomputing.org_SC21_sess166_pap450@linklings.com
SUMMARY:Exploiting User Activeness for Data Retention in HPC Systems
DESCRIPTION:Paper\n\nExploiting User Activeness for Data Retention in HPC 
 Systems\n\nZhang, Byna, Sim, Lee, Vazhkudai...\n\nHPC systems typically re
 ly on the fixed-lifetime (FLT) data retention strategy, which only conside
 rs temporal locality of data accesses to parallel file systems. Our extens
 ive analysis based on the leadership-class HPC system traces, however, sug
 gests that the FLT approach often fails to capture the dynamics in users' 
 behavior and leads to undesired data purge. In this study, we propose an a
 ctiveness-based data retention (ActiveDR) solution, which advocates consid
 ering the data retention approach from a holistic activeness-based perspec
 tive. By evaluating the frequency and impact of users' activities, ActiveD
 R prioritizes the file purge process for inactive users and rewards active
  users with extended file lifetime on parallel storage. Our extensive eval
 uations based on the traces of the prior Titan supercomputer show that, wh
 en reaching the same purge target, ActiveDR achieves up to 37% file miss r
 eduction as compared to the current FLT retention methodology.\n\nTag: Rep
 roducibility Badge, Applications, Big Data, Datacenter, File Systems and I
 /O, Machine Learning and Artificial Intelligence, State of the Practice, S
 torage\n\nRegistration Category: Tech Program Reg Pass\n\nReproducibility 
 Badges: Artifact Available, Artifact Functional
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