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DTSTAMP:20260522T150122Z
LOCATION:D170
DTSTART;TZID=America/Chicago:20181111T105200
DTEND;TZID=America/Chicago:20181111T111400
UID:submissions.supercomputing.org_SC18_sess149_ws_mchpc106@linklings.com
SUMMARY:Evaluation of Intel Memory Drive Technology Performance for Scient
 ific Applications
DESCRIPTION:Vladimir Mironov (Lomonosov Moscow State University), Andrey K
 udryavtsev (Intel Corporation), Yuri Alexeev (Argonne National Laboratory)
 , Alexander Moskovsky (RSC Technologies), and Igor Kulikov and Igor Cherny
 kh (Institute of Computational Mathematics and Mathematical Geophysics SB 
 RAS)\n\nIn this paper, we present benchmark data for Intel Memory Drive Te
 chnology (IMDT), which is a new generation of Software-defined Memory (SDM
 ) based on Intel ScaleMP collaboration and using 3D XPoint TM based Intel 
 Solid-State Drives (SSDs) called Optane. We studied IMDT performance for s
 ynthetic benchmarks, scientific kernels, and applications. We chose these 
 benchmarks to represent different patterns for computation and accessing d
 ata on disks and memory. To put performance of IMDT in comparison, we used
  two memory configurations: hybrid IMDT DDR4/Optane and DDR4 only systems.
  The performance was measured as a percentage of used memory and analyzed 
 in detail. We found that for some applications DDR4/Optane hybrid configur
 ation outperforms DDR4 setup by up to 20%\n\nTag: Memory, NVRAM, Parallel 
 Programming Languages, Libraries, and Models\n\nRegistration Category: Wor
 kshop Reg Pass\n\nSession Chairs: Ron Brightwell (Sandia National Laborato
 ries); Maya Gokhale (Lawrence Livermore National Laboratory (LLNL)); Xian-
 He Sun (Illinois Institute of Technology); and Yonghong Yan (University of
  North Carolina, Charlotte)\n\n
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