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DTSTAMP:20210916T132529Z
LOCATION:Ernesto Bertarelli
DTSTART;TZID=Europe/Stockholm:20210705T133000
DTEND;TZID=Europe/Stockholm:20210705T150000
UID:submissions.pasc-conference.org_PASC21_sess106@linklings.com
SUMMARY:AP03 - ACM Papers
DESCRIPTION:Paper\n\nIn-Situ Assessment of Device-Side Compute Work for Dy
 namic Load Balancing in a GPU-Accelerated PIC Code\n\nRowan, Huebl, Gott, 
 Deslippe, Thévenet...\n\nMaintaining computational load balance is importa
 nt to the performant behavior of codes which operate under a distributed c
 omputing model. This is especially true for GPU architectures, which can s
 uffer from memory oversubscription if improperly load balanced. We present
  enhancements to traditional ...\n\n---------------------\nMemory Reductio
 n Using a Ring Abstraction over GPU RDMA for Distributed Quantum Monte Car
 lo Solver\n\nWei, D’Azevedo, Huck, Chatterjee, Hernandez...\n\nScientific 
 applications that run on leadership computing facilities often face the ch
 allenge of being unable to fit leading science cases onto accelerator devi
 ces due to memory constraints (memory-bound applications). In this work, t
 he authors studied one such US Department of Energy mission-critica...\n\n
 ---------------------\nBenchmarking of state-of-the-art HPC clusters with 
 a production CFD code\n\nBanchelli, Garcia-Gasulla, Houzeaux, Mantovani\n\
 nComputing technologies populating high-performance computing (HPC) cluste
 rs is getting more and more diverse, offering a wide range of architectura
 l features. As a consequence, efficient programming of such platforms beco
 mes a complex task. In this paper we provide a micro-benchmarking of three
  HPC ...\n\n\nDomain: Chemistry and Materials, Physics
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