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PanSim: A Performance-Portable Agent Based Model
SessionPoster Reception
DescriptionPanSim, a specialized agent-based model, was developed to analyze interventions against COVID-19. Implemented in C++ and Thrust, it is a highly performant and portable code. Here we focus on different algorithmic formulations for calculating cumulative values like infectiousness at different locations. A detailed comparison of time and efficiency on different CPUs and GPUs was conducted, revealing suboptimal parallel efficiency. The time to execute 704 simulations on each platform was evaluated, emphasizing overall throughput instead of latency for more taxing workloads. We benchmarked modern CPU and GPU architectures, revealing the superior performance of NVIDIA A100 and AMD Genoa-X platforms. Additionally, the monetary cost associated with executing the simulations was analyzed, presenting a contrasting landscape in on-demand and spot pricing. Ampere Altra platform emerged as the most cost-effective. The findings contribute to understanding the efficiency, time, and cost dynamics in modeling and provide insights for the practice of pandemic response planning.
Event Type
ACM Student Research Competition: Graduate Poster
ACM Student Research Competition: Undergraduate Poster
Doctoral Showcase
Posters
Research Posters
Scientific Visualization & Data Analytics Showcase
TimeTuesday, 14 November 20235:15pm - 7pm MST
LocationDEF Concourse
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