Global pandemics can wreak havoc and lead to significant social, economic, and personal losses. Preventing the spread of infectious diseases requires implementing interventions at different levels of government, and evaluating the potential impact and efficacy of those preemptive measures. Agent-based modeling can be used for detailed studies of epidemic diffusion and possible interventions. We present Loimos, a highly parallel simulation of epidemic diffusion written on top of Charm++, an asynchronous task-based parallel runtime. Loimos uses a hybrid of time-stepping and discrete-event simulation to model disease spread. We show that our implementation of Loimos is able to scale to upwards of a thousand cores on the Rivanna supercomputer at the University of Virginia
Slides will be available for download here after the presentation.
Joy Kitson is a fourth year PhD student in the Parallel Systems and Software Group at the University of Maryland, advised by Abhinav Bhatele. Her work revolves around devloping and optimising scientific applications for HPC, with a particular focus on computational epidemiology. Joy is a Department of Energy Computational Science Graduate Fellow, and has completed several internships at DoE labs, including most reccently at Oak Ridge National Lab in Teneessee