DeepABM: Scalable and Efficient Agent-Based Simulations Via Geometric Learning Frameworks-a Case Study for Covid-19 Spread and Interventions

Ayush Chopra, Ramesh Raskar, Jayakumar Subramanian, Balaji Krishnamurthy, Esma S. Gel, Santiago Romero-Brufau, Kalyan S. Pasupathy, Thomas C. Kingsley

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

We introduce DeepABM, a computational framework for agent-based modeling that leverages geometric message passing for simulating action and interactions over large agent populations. Using DeepABM allows scaling simulations to large agent populations in real-time and running them efficiently on GPU architectures. Using the DeepABM framework, we build DeepABM-COVID simulator to provide support for various non-pharmaceutical interventions (quarantine, exposure notification, vaccination, testing) for the COVID-19 pandemic, and can scale to populations of representative size in real-time on a GPU. DeepABM-COVID can model 200 million interactions (over 100,000 agents across 180 time-steps) in 90 seconds, and is made available online to help researchers with modeling and analysis of various interventions. We explain various components of the framework and discuss results from one research study to evaluate the impact of delaying the second dose of the COVID-19 vaccine in collaboration with clinical and public health experts.

Original languageEnglish (US)
Title of host publication2021 Winter Simulation Conference, WSC 2021
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781665433112
DOIs
StatePublished - 2021
Externally publishedYes
Event2021 Winter Simulation Conference, WSC 2021 - Phoenix, United States
Duration: Dec 12 2021Dec 15 2021

Publication series

NameProceedings - Winter Simulation Conference
Volume2021-December
ISSN (Print)0891-7736

Conference

Conference2021 Winter Simulation Conference, WSC 2021
Country/TerritoryUnited States
CityPhoenix
Period12/12/2112/15/21

ASJC Scopus subject areas

  • Software
  • Modeling and Simulation
  • Computer Science Applications

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