Distributed, parallel simulation of multiple, deliberative agents
PADS '00 Proceedings of the fourteenth workshop on Parallel and distributed simulation
A ghost cell expansion method for reducing communications in solving PDE problems
Proceedings of the 2001 ACM/IEEE conference on Supercomputing
Experiences creating three implementations of the repast agent modeling toolkit
ACM Transactions on Modeling and Computer Simulation (TOMACS)
Managing Business Complexity: Discovering Strategic Solutions with Agent-Based Modeling and Simulation
Proceedings of the 38th conference on Winter simulation
Distributed simulation of agent-based systems with HLA
ACM Transactions on Modeling and Computer Simulation (TOMACS)
Effective automatic parallelization of stencil computations
Proceedings of the 2007 ACM SIGPLAN conference on Programming language design and implementation
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
Performance Optimization for Multi-agent Based Simulation in Grid Environments
CCGRID '08 Proceedings of the 2008 Eighth IEEE International Symposium on Cluster Computing and the Grid
Stencil computation optimization and auto-tuning on state-of-the-art multicore architectures
Proceedings of the 2008 ACM/IEEE conference on Supercomputing
Performance modeling and automatic ghost zone optimization for iterative stencil loops on GPUs
Proceedings of the 23rd international conference on Supercomputing
Comparing Parallel Simulation of Social Agents Using Cilk and OpenCL
DS-RT '11 Proceedings of the 2011 IEEE/ACM 15th International Symposium on Distributed Simulation and Real Time Applications
A Latency-Hiding Algorithm for ABMS on Parallel/Distributed Computing Environment
PADS '12 Proceedings of the 2012 ACM/IEEE/SCS 26th Workshop on Principles of Advanced and Distributed Simulation
Simulation and study of large-scale bacteria-materials interactions via BioScape enabled by GPUs
Proceedings of the ACM Conference on Bioinformatics, Computational Biology and Biomedicine
A general-purpose graph dynamical system modeling framework
Proceedings of the Winter Simulation Conference
Interaction-based HPC modeling of social, biological, and economic contagions over large networks
Proceedings of the Winter Simulation Conference
Accelerating simulation of agent-based models on heterogeneous architectures
Proceedings of the 6th Workshop on General Purpose Processor Using Graphics Processing Units
Hybrid scheduling for event-driven simulation over heterogeneous computers
Proceedings of the 2013 ACM SIGSIM conference on Principles of advanced discrete simulation
Coordinator-master-worker model for efficient large scale network simulation
Proceedings of the 6th International ICST Conference on Simulation Tools and Techniques
Journal of Parallel and Distributed Computing
Designing an agent based model for the efficient removal of red imported fire ant colonies
Proceedings of the 2013 Summer Computer Simulation Conference
Multiagent and Grid Systems
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An effective latency-hiding mechanism is presented in the parallelization of agent-based model simulations (ABMS) with millions of agents. The mechanism is designed to accommodate the hierarchical organization as well as heterogeneity of current state-of-the-art parallel computing platforms. We use it to explore the computation vs. communication trade-off continuum available with the deep computational and memory hierarchies of extant platforms and present a novel analytical model of the tradeoff. We describe our implementation and report preliminary performance results on two distinct parallel platforms suitable for ABMS: CUDA threads on multiple, networked graphical processing units (GPUs), and pthreads on multi-core processors. Message Passing Interface (MPI) is used for inter-GPU as well as inter-socket communication on a cluster of multiple GPUs and multi-core processors. Results indicate the benefits of our latency-hiding scheme, delivering as much as over 100-fold improvement in runtime for certain benchmark ABMS application scenarios with several million agents. This speed improvement is obtained on our system that is already two to three orders of magnitude faster on one GPU than an equivalent CPU-based execution in a popular simulator in Java. Thus, the overall execution of our current work is over four orders of magnitude faster when executed on multiple GPUs.