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DTSTAMP:20260522T150127Z
LOCATION:C140/142
DTSTART;TZID=America/Chicago:20181114T133000
DTEND;TZID=America/Chicago:20181114T150000
UID:submissions.supercomputing.org_SC18_sess204@linklings.com
SUMMARY:Physics and Tensor Applications
DESCRIPTION:Accelerating Quantum Chemistry with Vectorized and Batched Int
 egrals\n\nThis paper presents the first quantum chemistry calculations usi
 ng a recently developed vectorized library for computing electron repulsio
 n integrals. To lengthen the SIMD loop and thus improve SIMD utilization, 
 the approach used in this paper is to batch together the computation of mu
 ltiple integra...\n\n\nHua Huang and Edmond Chow (Georgia Institute of Tec
 hnology)\n---------------------\nSimulating the Wenchuan Earthquake with A
 ccurate Surface Topography on Sunway TaihuLight\n\nThis paper reports our 
 efforts on performing 50-m resolution earthquake simulation of the Wenchua
 n Earthquake (Ms 8.0, China) on Sunway TaihuLight. To accurately capture t
 he surface topography, we adopt a curvilinear grid finite-difference metho
 d with a traction image free surface implementation and...\n\n\nBingwei Ch
 en, Haohuan Fu, Yanwen Wei, and Conghui He (Tsinghua University; National 
 Supercomputing Center, Wuxi); Wenqiang Zhang (University of Science and Te
 chnology of China); Yuxuan Li (Tsinghua University; National Supercomputin
 g Center, Wuxi); Wubin Wan and Wei Zhang (National Supercomputing Center, 
 Wuxi); Lin Gan (Tsinghua University; National Supercomputing Center, Wuxi)
 ; Wei Zhang and Zhenguo Zhang (Southern University of Science and Technolo
 gy, China); Guangwen Yang (Tsinghua University; National Supercomputing Ce
 nter, Wuxi); and Xiaofei Chen (Southern University of Science and Technolo
 gy, China)\n---------------------\nHigh-Performance Dense Tucker Decomposi
 tion on GPU Clusters\n\nThe Tucker decomposition method is one of the most
  popular algorithms for analyzing and compressing data with multi-way rela
 tionship. Its execution time is typically dominated by dense matrix multip
 lication, which makes it well-suited for GPU acceleration. State-of-the-ar
 t distributed dense Tucker i...\n\n\nJee Choi (IBM), Xing Liu (Intel Corpo
 ration), and Venkatesan Chakaravarthy (IBM)\n\nTag: Algorithms, Applicatio
 ns, Computational Physics, Scientific Computing\n\nRegistration Category: 
 Tech Program Reg Pass\n\nSession Chair: Erik Draeger (Lawrence Livermore N
 ational Laboratory (LLNL), Center for Applied Scientific Computing)
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