Title :
A flexible, large-scale, distributed agent based epidemic model
Author_Institution :
Brookings Instn., Washington
Abstract :
We describe a distributed agent based epidemic model that is capable of easily simulating several hundred million agents. The model is adaptable to shared-memory and distributed-memory architectures. Several problems are addressed to enable the distributed simulation: allocation of agents to available compute nodes, periodic synchronization of compute nodes, and efficient communication between compute nodes. We assert that our modeling scheme is easily adaptable to different hardware environments and does not require large investments in performance tuning or special case coding.
Keywords :
distributed shared memory systems; software agents; software architecture; distributed agent; distributed-memory architectures; epidemic model; performance tuning; shared-memory architectures; special case coding; Central Processing Unit; Computational modeling; Computer architecture; Delay; Diseases; Distributed computing; Environmental economics; Java; Large-scale systems; Yarn;
Conference_Titel :
Simulation Conference, 2007 Winter
Conference_Location :
Washington, DC
Print_ISBN :
978-1-4244-1306-5
Electronic_ISBN :
978-1-4244-1306-5
DOI :
10.1109/WSC.2007.4419769
