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DTSTART:19700308T020000
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BEGIN:VEVENT
DTSTAMP:20210402T160550Z
LOCATION:Poster Module
DTSTART;TZID=America/New_York:20201119T083000
DTEND;TZID=America/New_York:20201119T170000
UID:submissions.supercomputing.org_SC20_sess341_spostg102@linklings.com
SUMMARY:Activeness-Based Data Retention Recommender for HPC Facilities
DESCRIPTION:ACM Student Research Competition: Graduate Poster, ACM Student
  Research Competition: Undergraduate Poster, Posters\n\nActiveness-Based D
 ata Retention Recommender for HPC Facilities\n\nZhang\n\nThe storage syste
 m of many high-performance computing (HPC) facilities faces an increasingl
 y challenging goal of meeting unlimited data growth with limited storage c
 apacity growth. The data retention policy plays a vital role in addressing
  such challenge. However, most existing data retention policies are design
 ed based on and biased towards the temporal properties of files rather tha
 n the activities of users. Such biased data retention policies may cause u
 nnecessary data interruption or even data loss to users. In this study, we
  propose a data retention action recommender system (DataRecommender) that
  generates user-centric data retention recommendations based on a holistic
  view of the user activeness. Our evaluation on the recommendation results
  shows that, as compared to the existing data retention policies, adopting
  DataRecommender’s data retention recommendation can significantly avoid u
 ndesired data loss for active users while maintaining the same ability of 
 cleaning unnecessary files as compared to existing LRU-based data retentio
 n policies.\n\nTag: Student Program\n\nRegistration Category: Tech Program
  Reg Pass, Exhibits Reg Pass
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