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UID:submissions.supercomputing.org_SC23_sess177_pap300@linklings.com
SUMMARY:ANT-MOC: Scalable Neutral Particle Transport Using 3D Method of Ch
 aracteristics on Multi-GPU Systems
DESCRIPTION:Shunde Li and Zongguo Wang (Computer Network Information Cente
 r, Chinese Academy of Sciences); Lingkun Bu (National Center for Materials
  Service Safety, University of Science and Technology Beijing); Jue Wang a
 nd Zhikuang Xin (Computer Network Information Center, Chinese Academy of S
 ciences); Shigang Li (School of Computer Science, Beijing University of Po
 sts and Telecommunications); Yangang Wang and Yangde Feng (Computer Networ
 k Information Center, Chinese Academy of Sciences); Peng Shi (National Cen
 ter for Materials Service Safety, University of Science and Technology Bei
 jing); Yun Hu (China Institute of Atomic Energy); and Xuebin Chi (Computer
  Network Information Center, Chinese Academy of Sciences)\n\nThe Method Of
  Characteristic (MOC) to solve the Neutron Transport Equation (NTE) is the
  core of full-core simulation for reactors. High resolution is enabled by 
 discretizing the NTE through massive tracks to traverse the 3D reactor geo
 metry. However, the 3D full-core simulation is prohibitively expensive bec
 ause of the high memory consumption and the severe load imbalance. To deal
  with these challenges, we develop ANT-MOC. Specifically, we build a perfo
 rmance model for memory footprint, computation and communication, based on
  which a track management strategy is proposed to overcome the resolution 
 bottlenecks caused by limited GPU memory. Furthermore, we implement a nove
 l multi-level load mapping strategy to ensure load balancing among nodes, 
 GPUs, and CUs. ANT-MOC enables a 3D full-core reactor simulation with 100 
 billion tracks on 16,000 GPUs, with 70.69% and 89.38% parallel efficiency 
 for strong scalability and weak scalability, respectively.\n\nTag: Acceler
 ators, Applications, Modeling and Simulation\n\nRegistration Category: Tec
 h Program Reg Pass\n\nAward Finalist: Best Paper Finalist, Best Student Pa
 per Finalist\n\nReproducibility Badges: Artifact Available, Artifact Funct
 ional, Results Reproduced\n\nSession Chair: Sameh Abdulah (King Abdullah U
 niversity of Science and Technology (KAUST))\n\n
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