The Global-Scale Agent Model (GSAM) is presented. The GSAM is a high-performance distributed platform for agent-based epidemic modeling capable of simulating a disease outbreak in a population of several billion agents. It is unprecedented in its scale, its speed, and its use of Java. Solutions to multiple challenges inherent in distributing massive agent-based models are presented. Communication, synchronization, and memory usage are among the topics covered in detail. The memory usage discussion is Java specific. However, the communication and synchronization discussions apply broadly. We provide benchmarks illustrating the GSAM’s speed and scalability.
Description
A Distributed Platform for Global-Scale Agent-Based Models of Disease Transmission
%0 Journal Article
%1 Parker:2011:tomacs
%A Parker, Jon
%A Epstein, Joshua M.
%C New York, NY, USA
%D 2011
%I ACM
%J ACM Transactions on Modeling and Computer Simulation
%K epidemes
%N 1
%P 2:1-25
%R 10.1145/2043635.2043637
%T A Distributed Platform for Global-Scale Agent-Based Models of Disease Transmission
%V 22
%X The Global-Scale Agent Model (GSAM) is presented. The GSAM is a high-performance distributed platform for agent-based epidemic modeling capable of simulating a disease outbreak in a population of several billion agents. It is unprecedented in its scale, its speed, and its use of Java. Solutions to multiple challenges inherent in distributing massive agent-based models are presented. Communication, synchronization, and memory usage are among the topics covered in detail. The memory usage discussion is Java specific. However, the communication and synchronization discussions apply broadly. We provide benchmarks illustrating the GSAM’s speed and scalability.
@article{Parker:2011:tomacs,
abstract = {The Global-Scale Agent Model (GSAM) is presented. The GSAM is a high-performance distributed platform for agent-based epidemic modeling capable of simulating a disease outbreak in a population of several billion agents. It is unprecedented in its scale, its speed, and its use of Java. Solutions to multiple challenges inherent in distributing massive agent-based models are presented. Communication, synchronization, and memory usage are among the topics covered in detail. The memory usage discussion is Java specific. However, the communication and synchronization discussions apply broadly. We provide benchmarks illustrating the GSAM’s speed and scalability.},
acmid = {2043637},
added-at = {2017-03-16T11:32:53.000+0100},
address = {New York, NY, USA},
articleno = {2},
author = {Parker, Jon and Epstein, Joshua M.},
biburl = {https://www.bibsonomy.org/bibtex/2ee654a8b1ccfdc9ac50e5d7d6f839920/krevelen},
description = {A Distributed Platform for Global-Scale Agent-Based Models of Disease Transmission},
doi = {10.1145/2043635.2043637},
interhash = {e342d81a6b31470b871b3912378a2919},
intrahash = {ee654a8b1ccfdc9ac50e5d7d6f839920},
issn = {1049-3301},
issue_date = {December 2011},
journal = {ACM Transactions on Modeling and Computer Simulation },
keywords = {epidemes},
month = dec,
number = 1,
numpages = {25},
pages = {2:1-25},
publisher = {ACM},
timestamp = {2017-03-16T11:32:53.000+0100},
title = {A Distributed Platform for Global-Scale Agent-Based Models of Disease Transmission},
volume = 22,
year = 2011
}