Parallel discrete event simulation
Communications of the ACM - Special issue on simulation
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IEEE Transactions on Computers
PVM: Parallel virtual machine: a users' guide and tutorial for networked parallel computing
PVM: Parallel virtual machine: a users' guide and tutorial for networked parallel computing
Dynamic load balancing strategies for conservative parallel simulations
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Dynamic load balancing in parallel discrete event simulation for spatially explicit problems
PADS '98 Proceedings of the twelfth workshop on Parallel and distributed simulation
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Journal of Parallel and Distributed Computing - Parallel and Distributed Discrete Event Simulation--An Emerging Technology
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Winter Simulation Conference
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PADS '11 Proceedings of the 2011 IEEE Workshop on Principles of Advanced and Distributed Simulation
Partitioning on Dynamic Behavior for Parallel Discrete Event Simulation
PADS '12 Proceedings of the 2012 ACM/IEEE/SCS 26th Workshop on Principles of Advanced and Distributed Simulation
Cybersim: geographic, temporal, and organizational dynamics of malware propagation
Proceedings of the Winter Simulation Conference
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We re-examine the problem of load balancing in conservatively synchronized parallel, discrete- event simulations executed on high-performance computing clusters, focusing on simulations where computational and messaging load tend to be spatially clustered. Such domains are frequently characterized by the presence of geographic "hot-spots'' - regions that generate significantly more simulation events than others. Examples of such domains include simulation of urban regions, transportation networks and networks where interaction between entities is often constrained by physical proximity. Noting that in conservatively synchronized parallel simulations, the speed of execution of the simulation is determined by the slowest ( i.e most heavily loaded) simulation process, we study different partitioning strategies in achieving equitable processor-load distribution in domains with spatially clustered load. In particular, we study the effectiveness of partitioning via spatial scattering to achieve optimal load balance. In this partitioning technique, nearby entities are explicitly assigned to different processors, thereby scattering the load across the cluster. This is motivated by two observations, namely, (i) since load is spatially clustered, spatial scattering should, intuitively, spread the load across the compute cluster, and (ii) in parallel simulations, equitable distribution of CPU load is a greater determinant of execution speed than message passing overhead. Through large-scale simulation experiments - both of abstracted and real simulation models - on high performance clusters, we observe that scatter partitioning - even with its greatly increased messaging overhead - often significantly outperforms more conventional spatial partitioning techniques that seek to reduce messaging overhead. Further, even if hot-spots change over the course of the simulation, if the underlying feature of spatial clustering is retained, load continues to be balanced with spatial scattering leading us to the observation that spatial scattering can often obviate the need for dynamic load balancing.