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DTSTART:19700308T020000
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DTSTAMP:20260522T150116Z
LOCATION:C2/3/4 Ballroom
DTSTART;TZID=America/Chicago:20181113T083000
DTEND;TZID=America/Chicago:20181113T170000
UID:submissions.supercomputing.org_SC18_sess322_post167@linklings.com
SUMMARY:Enabling Data Analytics Workflows Using Node-Local Storage
DESCRIPTION:Tu Mai Anh Do (University of Southern California, Information 
 Sciences Institute); Ming Jiang, Brian Gallagher, Albert Chu, and Cyrus Ha
 rrison (Lawrence Livermore National Laboratory); and Karan Vahi and Ewa De
 elman (University of Southern California, Information Sciences Institute)\
 n\nThe convergence of high-performance computing (HPC) and Big Data is a n
 ecessity with the push toward extreme-scale computing. As HPC simulations 
 become more complex, the analytics need to process larger amounts of data,
  which poses significant challenges for coupling HPC simulations with Big 
 Data analytics. This poster presents a novel node-local approach that uses
  a workflow management system (WMS) to enable the coupling between the sim
 ulations and the analytics in scientific workflows by leveraging node-loca
 l non-volatile random-access memory (NVRAM).\n\nRegistration Category: Tec
 h Program Reg Pass, Exhibits Reg Pass\n\n
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