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BEGIN:VEVENT
DTSTAMP:20211207T055400Z
LOCATION:Second Floor Atrium
DTSTART;TZID=America/Chicago:20211118T083000
DTEND;TZID=America/Chicago:20211118T170000
UID:submissions.supercomputing.org_SC21_sess243_spostu102@linklings.com
SUMMARY:Productive, Performant, and Parallel Generic Lossy Data Compressio
 n with LibPressio
DESCRIPTION:ACM Student Research Competition: Graduate Poster, ACM Student
  Research Competition: Undergraduate Poster, Posters\n\nProductive, Perfor
 mant, and Parallel Generic Lossy Data Compression with LibPressio\n\nMalvo
 so\n\nData compression is vital in scientific applications because it redu
 ces the size of files. This is important because running experiments on th
 e data and storing it requires significantly less time and memory. In an e
 ffort to create more  efficiency, LibPressio was created as a single inter
 face to utilize multiple different compressors. This interface eliminates 
 the need for generating large amounts of code to be able to switch between
  compressors. This is useful because time spent editing code could be used
  running more experiments.  The goal of our testing is to evaluate metrics
  when using LibPressio as compared to not using it to determine performanc
 e. We evaluate how much LibPressio is able to reduce the size of the origi
 nal file, as well as how long it takes to compress the data. We also evalu
 ate the parallel performance of LibPressio. These are assessed in order to
  determine if the abstraction improves efficiency.\n\nTag: In-Person Only\
 n\nRegistration Category: Tech Program Reg Pass, Exhibit Hall Only
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