A Distributed Platform for Global-Scale Agent-Based Models of Disease Transmission
Jon Parker1, Joshua M Epstein1
1The Johns Hopkins University.
ACM Transactions on Modeling and Computer Simulation : a Publication of the Association for Computing Machinery
|January 28, 2014
Summary
The Global-Scale Agent Model (GSAM) enables large-scale, high-speed epidemic simulations. This Java-based platform addresses challenges in distributing massive agent models for disease outbreak research.
Area of Science:
- Computer Science
- Epidemiology
- Computational Science
Background:
- Agent-based modeling is crucial for simulating complex systems like disease outbreaks.
- Existing platforms often struggle with the computational demands of simulating billions of agents.
- High-performance computing is essential for realistic epidemic simulations.
Purpose of the Study:
- To introduce the Global-Scale Agent Model (GSAM), a novel distributed platform for large-scale agent-based epidemic modeling.
- To present solutions for challenges in distributing massive agent-based models.
- To demonstrate the speed and scalability of the GSAM platform.
Main Methods:
- Development of a high-performance distributed platform using Java.
- Implementation of strategies for efficient communication and synchronization in distributed agent models.
- Optimization of memory usage for large-scale simulations.
- Benchmarking to evaluate performance and scalability.
Main Results:
- The GSAM platform demonstrates unprecedented scale, simulating billions of agents.
- Benchmarks confirm the platform's high speed and scalability.
- Effective solutions for communication, synchronization, and memory management in distributed agent models were developed.
Conclusions:
- The GSAM provides a powerful tool for large-scale epidemic simulations.
- The presented solutions enhance the feasibility of distributed agent-based modeling.
- The platform's performance supports advanced research in disease outbreak dynamics.
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