Multilevel k-way partitioning scheme for irregular graphs
Journal of Parallel and Distributed Computing
Large Scale Distributed Simulation on the Grid
CCGRID '06 Proceedings of the Sixth IEEE International Symposium on Cluster Computing and the Grid
Efficient agent-based simulation framework for multi-node supercomputers
Proceedings of the 38th conference on Winter simulation
X10: concurrent programming for modern architectures
Proceedings of the 12th ACM SIGPLAN symposium on Principles and practice of parallel programming
A platform for massive agent-based simulation and its evaluation
Proceedings of the 6th international joint conference on Autonomous agents and multiagent systems
A flexible, large-scale, distributed agent based epidemic model
Proceedings of the 39th conference on Winter simulation: 40 years! The best is yet to come
Large scale agent-based simulation on the grid
Future Generation Computer Systems
Dynamic level of detail for large scale agent-based urban simulations
The 10th International Conference on Autonomous Agents and Multiagent Systems - Volume 2
X10-based massive parallel large-scale traffic flow simulation
Proceedings of the 2012 ACM SIGPLAN X10 Workshop
Proceedings of the Winter Simulation Conference
Extreme big data processing in large-scale graph analytics and billion-scale social simulation
Proceedings of the 5th ACM/SPEC international conference on Performance engineering
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This paper describes highly scalable X10-based agent simulation platform called XAXIS. XAXIS is designed to handle millions or billions of agents on recent highly distributed and parallel computing environments with more than hundreds of CPU cores. To make the runtime scalable on such environments, we need to redesign and implement the simulation middleware. In this paper, we propose the software design, implementation on X10, one of the state-of-the-art PGAS language, and then application to large-scale traffic simulation. By using 192 CPU cores in distributed memory computing environment, the performance scalability is achieved with a traffic simulation.