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DTSTART;TZID=America/Denver:20231115T100000
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UID:submissions.supercomputing.org_SC23_sess303_rpost102@linklings.com
SUMMARY:Characterizing the Performance of the Implicit Massively Parallel 
 Particle-in-Cell iPIC3D Code
DESCRIPTION:Jeremy Johnathan Williams, Daniel Medeiros, Ivy Peng, and Stef
 ano Markidis (KTH Royal Institute of Technology, Sweden)\n\nOptimizing iPI
 C3D, an implicit Particle-in-Cell (PIC) code, for large-scale 3D plasma si
 mulations is crucial for space and astrophysical applications. This work f
 ocuses on characterizing iPIC3D’s communication efficiency through strateg
 ic measures like optimal node placement, communication and computation ove
 rlap, and load balancing. Profiling and tracing tools are employed to anal
 yze iPIC3D’s communication efficiency and provide practical recommendation
 s. Implementing optimized communication protocols addresses the Geospace E
 nvironmental Modeling (GEM) magnetic reconnection challenges in plasma phy
 sics with more precise simulations. This approach captures the complexitie
 s of 3D plasma simulations, particularly in magnetic reconnection, advanci
 ng space and astrophysical research.\n\nTag: Artificial Intelligence/Machi
 ne Learning, Architecture and Networks, Heterogeneous Computing, I/O and F
 ile Systems, Performance Measurement, Modeling, and Tools, Post-Moore Comp
 uting, Programming Frameworks and System Software, Quantum Computing\n\nRe
 gistration Category: Tech Program Reg Pass, Exhibits Reg Pass\n\n
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