Parallel discrete event simulation
Communications of the ACM - Special issue on simulation
On a parallel partitioning technique for use with conservative parallel simulation
PADS '93 Proceedings of the seventh workshop on Parallel and distributed simulation
A static partitioning and mapping algorithm for conservative parallel simulations
PADS '94 Proceedings of the eighth workshop on Parallel and distributed simulation
GTW: a time warp system for shared memory multiprocessors
WSC '94 Proceedings of the 26th conference on Winter simulation
Experiments in automated load balancing
PADS '96 Proceedings of the tenth workshop on Parallel and distributed simulation
A framework for performance analysis of parallel discrete event simulators
Proceedings of the 29th conference on Winter simulation
Dynamic load balancing strategies for conservative parallel simulations
Proceedings of the eleventh workshop on Parallel and distributed simulation
Hierarchical partitioning algorithm for optimistic distributed simulation of DEVS models
Journal of Systems Architecture: the EUROMICRO Journal - Special double issue: parallel and distributed simulation
Parallel discrete event simulation on shared-memory multiprocessors
ANSS '91 Proceedings of the 24th annual symposium on Simulation
On the origin of power laws in Internet topologies
ACM SIGCOMM Computer Communication Review
WARPED: A Time Warp Simulation Kernel for Analysis and Application Development
HICSS '96 Proceedings of the 29th Hawaii International Conference on System Sciences Volume 1: Software Technology and Architecture
BRITE: An Approach to Universal Topology Generation
MASCOTS '01 Proceedings of the Ninth International Symposium in Modeling, Analysis and Simulation of Computer and Telecommunication Systems
A first-principles approach to understanding the internet's router-level topology
Proceedings of the 2004 conference on Applications, technologies, architectures, and protocols for computer communications
A non-fragmenting partitioning algorithm for hierarchical models
Proceedings of the 38th conference on Winter simulation
Scaling time warp-based discrete event execution to 104 processors on a Blue Gene supercomputer
Proceedings of the 4th international conference on Computing frontiers
A Design-Driven Partitioning Algorithm for Distributed Verilog Simulation
Proceedings of the 21st International Workshop on Principles of Advanced and Distributed Simulation
A Flexible Dynamic Partitioning Algorithm for Optimistic Distributed Simulation
Proceedings of the 21st International Workshop on Principles of Advanced and Distributed Simulation
PADS '10 Proceedings of the 2010 IEEE Workshop on Principles of Advanced and Distributed Simulation
Can PDES scale in environments with heterogeneous delays?
Proceedings of the 2013 ACM SIGSIM conference on Principles of advanced discrete simulation
Interference resilient PDES on multi-core systems: towards proportional slowdown
Proceedings of the 2013 ACM SIGSIM conference on Principles of advanced discrete simulation
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Partitioning plays an important role in PDES performance due to the high communication cost in parallel platforms and the fine-granularity of most simulation models. Traditionally, models are partitioned by deriving the static communication graph of objects and applying graph partitioning to reduce the mincut while load balancing the number of objects. However, many, if not all, models exhibit great diversity in their dynamic behavior: objects communicate with each other with diverse frequencies that are commonly power-law distributed. Similar diversity exists in the activity of objects and the processing requirements of events. In this paper, we argue that partitioning based on static graphs ignores these effects, leading to poor partitioning. We explore how partitioning based on dynamic information should be approached and explore policies that focus on communication cost, load balancing and both. We show that on multicore clusters, dynamic partitioning achieves up to 4x better performance than static partitioning. On the AMD magnycours, where the communication latency is low, dynamic partitioning results in a 2x performance improvement over static partitioning for some of our models. Our future work considers how to derive the dynamic weights (in this study, we do that through profiling), and how to balance the importance of communication and computation in a way that is informed by the underlying architecture.