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DTSTAMP:20260522T150118Z
LOCATION:C2/3/4 Ballroom
DTSTART;TZID=America/Chicago:20181113T083000
DTEND;TZID=America/Chicago:20181113T170000
UID:submissions.supercomputing.org_SC18_sess322_post148@linklings.com
SUMMARY:Using Thrill to Process Scientific Data on HPC
DESCRIPTION:Mariia Karabin (Clemson University, Los Alamos National Labora
 tory); Xinyu Chen (University of New Mexico); Supreeth Suresh (University 
 of Wyoming); Ivo Jimenez (University of California, Santa Cruz); and Li-Ta
  Lo and Pascal Grosset (Los Alamos National Laboratory)\n\nWith ongoing im
 provement of computational power and memory capacity, the volume of scient
 ific data keeps growing. To gain insights from vast amounts of data, scien
 tists are starting to look at Big Data processing and analytics tools such
  as Apache Spark. In this poster, we explore Thrill, a framework for big d
 ata computation on HPC clusters that provides an interface similar to syst
 ems like Apache Spark but delivers higher performance since it is built on
  C++ and MPI. Using Thrill, we implemented several analytics operations to
  post-process and analyze data from plasma physics and molecular dynamics 
 simulations. Those operations were implemented with less programming effor
 t than hand-crafted data processing programs would require and obtained pr
 eliminary results which were verified by scientists at LANL.\n\nRegistrati
 on Category: Tech Program Reg Pass, Exhibits Reg Pass\n\n
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