The design and utilisation of PanSim, a portable pandemic simulator

The COVID-19 pandemic has presented a clear and present need for urgent decision making. Set in an environment of uncertain and unreliable data, and a diverse range of possible interventions, there is an obvious need for integrating HPC into workflows that include model calibration, and the exploration of the decision space. In this paper, we present the design of PanSim, a portable, performant, and productive agent-based simulator, which has been extensively used to model and forecast the pandemic in Hungary. We show its performance and scalability on CPUs and GPUs, then we discuss the workflows PanSim integrates into. We describe the heterogeneous, resource-constrained HPC environment available to us, and formulate a scheduling optimisation problem, as well as heuristics to solve them, to either minimise the execution time of a given number of simulations or to maximise the number of simulations executed in a given time frame.

Automated summary

The COVID-19 pandemic has created an urgent need for decision making, which requires integrating high-performance computing (HPC) into workflows for model calibration and decision space exploration. This paper presents the design of PanSim, a portable and efficient agent-based simulator used extensively for modeling and forecasting the pandemic in Hungary. The performance and scalability of PanSim on CPUs and GPUs are demonstrated, and the integrated workflows are discussed.