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DTSTART;TZID=America/Denver:20231113T153000
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UID:submissions.supercomputing.org_SC23_sess458_ws_mtsa107@linklings.com
SUMMARY:Accelerating In Situ Analysis Using Non-volatile Memory
DESCRIPTION:Deepak B. Hegde and Preeti Malakar (Indian Institute of Techno
 logy (IIT), Kanpur)\n\nThe relatively slower data transfer speeds resultin
 g in I/O bottlenecks in scientific simulations is one of the critical chal
 lenges in exascale computing. Simulations generate large data and analysis
  applications consume this data to provide time-critical insights. The lim
 ited size and high power consumption of Dynamic Random Access Memory (DRAM
 ) capacity leaves slow storage devices as the primary option for large-sca
 le data transfers. Non-volatile memory (NVM) devices such as Intel Optane 
 bridges the gap between storage and volatile memory by providing DRAM-comp
 arable performance and persistence. We present PQueue, a data transfer lib
 rary for in situ analysis of simulation output using persistent memory. PQ
 ueue leverages NVM and provides an API that resembles high-level parallel 
 I/O libraries such as PnetCDF to enable seamless transition for applicatio
 n developers. We achieved a maximum of 7X improvement in write times and a
  maximum of 10X improvement in read times as compared to PnetCDF.\n\nTag: 
 Applications, Architecture and Networks, Data Movement and Memory, Heterog
 eneous Computing, I/O and File Systems, Large Scale Systems, Middleware an
 d System Software, Performance Measurement, Modeling, and Tools, Performan
 ce Optimization\n\nRegistration Category: Workshop Reg Pass\n\nSession Cha
 irs: Tyler Allen (NVIDIA), Ron Brightwell (Sandia National Laboratories), 
 Maya Gokhale (Lawrence Livermore National Laboratory (LLNL)), and Ivy Peng
  (KTH Royal Institute of Technology)\n\n
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