MASS: A Parallelizing Library for Multi-Agent Spatial Simulation

Synopsis:

For more than the last two decades, multi-agent simulations have been highlighted to model mega-scale social or biological agents and to simulate their emergent collective behavior that may be difficult only with mathematical and macroscopic approaches. A successful key for simulating megascale agents is to speed up the execution with parallelization. Although many parallelization attempts have been made to multiagent simulations, most work has been done on shared-memory programming environments such as OpenMP, CUDA, and Global Array, or still has left several programming problems specific to distributed-memory systems, such as machine unawareness, ghost space management, and cross-processor agent management (including migration, propagation, and termination). To address these parallelization challenges, we have been developing MASS, a new parallel-computing library for multi-agent and spatial simulation over a cluster of computing nodes. MASS composes a user application of distributed arrays and multi-agents, each representing an individual simulation place or an active entity. All computation is enclosed in each array element or agent; all communication is scheduled as periodic data exchanges among those entities, using machine-independent identifiers; and agents migrate to a remote array element for rendezvousing with each other. Our unique agent-based approach takes advantage of these merits for parallelizing big data analysis using climate change and biological network motif searches as well as individual-based simulation such as neural network simulation and influenza epidemic simulation as practical application examples.

Members:

Summer 2012 Lab Members Summer 2013 Lab Members Winter 2014 Poster Presentation Autumn 2014 Lab Members

Manuals:

  1. MASS Java: Parallel-Computing Library for Multi-Agent Spatial Simulation, May 7th, 2010
  2. MASS C++: Parallel-Computing Library for Multi-Agent Spatial Simulation, January 30th, 2014
  3. MASS Cuda: Parallel-Computing Library for Multi-Agent Spatial Simulation, March 23rd, 2014

Software Downloading:

The latest Java version is currently available for internal use only in CSS497, 499, 534, 595, 596, 600 and 700.

Publications:

  1. Timothy Chuang, Munehiro Fukuda, A Parallel Multi-Agent Spatial Simulation Environment for Cluster Systems, In Proc. of the 16th IEEE International Conference on Computational Science and Engineering - CSE 2013, pages 143-150, Sydney, Australia, December 3-5, 2013
  2. Niko Simonson, Sean Wessels, Munehiro Fukuda, Language and Debugging Support for Multi-Agent and Spatial Simulation In Proc. of the 2012 International Conference on Parallel and Distributed Processing Techniques and Applications - PDPTA 2012, pages 373-379, Las Vegas, July 16 - 18, 2012
  3. Elad Mazurek, Munehiro Fukuda, A Parallelization of Orchard Temperature Predicting Programs In Proc. of 2011 IEEE Pacific Rim Conference on Communications, Computers and Signal Prcessing - PACRIM'11, pages 179-184, Victoria, BC, Canada, August 24-26, 2011
  4. John Emau, Timothy Chuang, Munehiro Fukuda, A Multi-Process Library for Multi-Agent and Spatial Simulation. In Proc. of 2011 IEEE Pacific Rim Conference on Communications, Computers and Signal Prcessing - PACRIM'11, pages 369-376, Victoria, BC, Canada, August 24-26, 2011

Presentation Slides:

  1. A Parallel Multi-Agent Spatial Simulation Environment for Cluster Systems (18 pages), the 16th IEEE International Conference on Computational Science and Engineering, Sydney, Australia, December 4, 2013
  2. MASS: A Multi-Agent Spatial Simulation Library (a one-Page flier), Office of Research - Undergraduate Research Fair, University of Washington Bothell, October 15, 2013
  3. MASS: A Multi-Agent Spatial Simulation Library (26 pages), Office of Research - Research in Progress, University of Washington, Bothell, April 23, 2013