A team led by Abhinav Bhatele of Lawrence Livermore National Laboratory is being honored for using NERSC resources to determine the scaling for a realistic simulation of an infectious disease on the national level. To predict how much processing power these simulations would take, the team ran experiments on various supercomputers, including NERSC’s Edison system, using the EpiSimDemics simulator, a highly scalable, parallel code written in Charm++ that uses agent-based modeling to simulate disease spreads over large, realistic, co-evolving interaction networks. This study will help future scientists predict and contain the spread of infectious diseases on the national scale. The other team members were Jae-Seung Yeom, Nikhil Jain, Chris Kuhlman, Yarden Livnat, Keith Bisset, Laxmikant Kale and Madhav Marathe.
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See AllOctober’s Charm++ Workshop included more than 20 talks and presentations on adaptivity in highly scalable parallel computing, recent results in adaptive runtime techniques in Charm++, and large-scale
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