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Collaborative Research: Elements: SciMem: Enabling High Performance Multi-Scale Simulation on Big Memory Platforms

Authors: Li, Zhen; Li, Dong; Ma, Yanbao; Shi, Liang;

Collaborative Research: Elements: SciMem: Enabling High Performance Multi-Scale Simulation on Big Memory Platforms

Abstract

This is the poster and lightning talk slide for 2022 CSSI PI Meeting. The goal of this project is to create a capability and a software package (named SciMem) that will enable high performance multi-scale simulation on big memory platforms. By designing SciMem as a library, we expect to bring a significant performance improvement for certain larger-scale multi-scale simulations widely applied in the fields of computational chemistry, fluid physics and material science, i.e., quantum mechanical/molecular mechanical-based molecular dynamics (MD) simulations.

{"references": ["Deng, Tushar, Bravo, Ghoshal, Karniadakis and Li, Theory and simulation of electrokinetic fluctuations in electrolyte solutions at the mesoscale. J. Fluid Mech., 2022. 942: A29.", "Xie, Dong, Liu, Peng, Ma and Li, MD-HM: memoization-based molecular dynamics simulations on big memory system, Proc. Int. Conf. Supercomput., 2021, Pages 215-226."]}

CSSI Award #2104116, #2103967.

Related Organizations
Keywords

molecular dynamics simulation, persistent memory, big memory computing

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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
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influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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impulse
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