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DTSTART;TZID=America/Denver:20231115T103000
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UID:submissions.supercomputing.org_SC23_sess176@linklings.com
SUMMARY:Applications in Materials Science and Biology
DESCRIPTION:Portable and Scalable All-Electron Quantum Perturbation Simula
 tions on Exascale Supercomputers\n\nQuantum perturbation theory is pivotal
  in determining the critical physical properties of materials. The first-p
 rinciples computations of these properties have yielded profound and quant
 itative insights in diverse domains of chemistry and physics.\n\nIn this w
 ork, we propose a portable and scalable Op...\n\n\nZhikun Wu, Yangjun Wu, 
 and Ying Liu (Institute of Computing Technology, Chinese Academy of Scienc
 es); Honghui Shang (University of Science and Technology of China); Yingxi
 ang Gao (National Supercomputer Center in Tianjin); Zhongcheng Zhang and Y
 uyang Zhang (Institute of Computing Technology, Chinese Academy of Science
 s); Yingchi Long (Institute of Computing Technology, Chinese Academy of Sc
 iences; Harbin Institute of Technology); and Xiaobing Feng and Huiming Cui
  (Institute of Computing Technology, Chinese Academy of Sciences)\n-------
 --------------\nEnhancing Adaptive Physics Refinement Simulations through 
 the Addition of Realistic Red Blood Cell Counts\n\nSimulations of cancer c
 ell transport require accurately modeling mm-scale and longer trajectories
  through a circulatory system containing trillions of deformable red blood
  cells, whose intercellular interactions require submicron fidelity. Using
  a hybrid CPU-GPU approach, we extend the advanced phys...\n\n\nSayan Royc
 howdhury, Samreen T. Mahmud, Aristotle Martin, Peter Balogh, and Daniel F.
  Puleri (Duke University); John Gounley (Oak Ridge National Laboratory (OR
 NL)); Erik W. Draeger (Lawrence Livermore National Laboratory (LLNL)); and
  Amanda Randles (Duke University)\n---------------------\nNNQS-Transformer
 : An Efficient and Scalable Neural Network Quantum States Approach for Ab 
 Initio Quantum Chemistry\n\nNeural network quantum state (NNQS) has emerge
 d as a promising candidate for quantum many-body problems, but its practic
 al applications are often hindered by the high cost of sampling and local 
 energy calculation.  We develop a high-performance NNQS method for ab init
 io electronic structure calculat...\n\n\nYangjun Wu (Institute of Computin
 g Technology, Chinese Academy of Sciences); Chu Guo (Hunan Normal Universi
 ty); Yi Fan (University of Science and Technology of China); Pengyu Zhou (
 Institute of Computing Technology, Chinese Academy of Sciences); and Hongh
 ui Shang (University of Science and Technology of China)\n\nTag: Applicati
 ons, Modeling and Simulation\n\nRegistration Category: Tech Program Reg Pa
 ss\n\nReproducibility Badges: Artifact Available, Artifact Functional\n\nS
 ession Chair: Hoon Ryu (KISTI)
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