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DTSTART:19700308T020000
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DTSTAMP:20181221T160730Z
LOCATION:C146
DTSTART;TZID=America/Chicago:20181113T163000
DTEND;TZID=America/Chicago:20181113T170000
UID:submissions.supercomputing.org_SC18_sess218_pap484@linklings.com
SUMMARY:Topology-Aware Space-Shared Co-Analysis of Large-Scale Molecular D
 ynamics Simulations
DESCRIPTION:Paper\nData Analytics, Performance, Programming Systems, Stora
 ge, Tools, Visualization, Tech Program Reg Pass\n\nTopology-Aware Space-Sh
 ared Co-Analysis of Large-Scale Molecular Dynamics Simulations\n\nMalakar,
  Munson, Knight, Vishwanath, Papka\n\nAnalysis of scientific simulation da
 ta can be concurrently executed with simulation either in time- or space-s
 hared mode. This mitigates the I/O bottleneck.  However it results in eith
 er stalling the simulation for performing the analysis or transferring dat
 a for analysis. In this paper, we improve the throughput of space-shared i
 n situ analysis of large-scale simulations by topology-aware mapping and o
 ptimal process decomposition. We propose node interconnect topology-aware 
 process placement for simulation and analysis to reduce the data movement 
 time. We also present an integer linear program for optimal 3D decompositi
 ons of simulation and analysis processes. We demonstrate our approach usin
 g molecular dynamics simulation on Mira, Cori and Theta supercomputers. Ou
 r mapping schemes, combined with optimal 3D process decomposition and code
  optimizations resulted in up to 30% lower execution times for space-share
 d in situ analysis than the default approach. Our mappings also reduce MPI
  collective I/O times by 10-40%.
URL:https://sc18.supercomputing.org/presentation/?id=pap484&sess=sess218
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