Scalable Framework for Agent-Based Computing

Project Details

Project Lead
Scott McCaulay 
Project Manager
Scott McCaulay 
Institution
Indiana University, UITS  
Discipline
Computer Science (401) 

Abstract

Prototyping a framework that will support a number of agent-based algorithms in a highly distributed and heterogeneous computing environment.

Intellectual Merit

Goal is to provide a simple solution to scale a wide variety of experiments in multiple fields. Examples of possible applications could include economic/market simulations, traffic or crowd flow control, network analysis.

Broader Impacts

Make significant computing resources accessible to communities of researchers who have historically not made use of HPC systems by simplifying access to scalability, while maximizing the usage of existing resources by distributing many short-duration jobs simultaneously to idle desktops, clusters, condor pools, etc.

Scale of Use

Modest and sporadic. To test scaling it would be ideal to have access to a large number (1000+) of cores simultaneously across multiple systems, but only required for a short duration (minutes).