Distributed discrete-event simulation
ACM Computing Surveys (CSUR)
Limitation of optimism in the time warp operating system
WSC '89 Proceedings of the 21st conference on Winter simulation
Parallel discrete event simulation
Communications of the ACM - Special issue on simulation
A study of time warp rollback mechanisms
ACM Transactions on Modeling and Computer Simulation (TOMACS)
Selecting the checkpoint interval in time warp simulation
PADS '93 Proceedings of the seventh workshop on Parallel and distributed simulation
An analytical comparison of periodic checkpointing and incremental state saving
PADS '93 Proceedings of the seventh workshop on Parallel and distributed simulation
The effect of memory capacity on Time Warp performance
Journal of Parallel and Distributed Computing - Special issue on parallel and discrete event simulation
Efficient algorithms for distributed snapshots and global virtual time approximation
Journal of Parallel and Distributed Computing - Special issue on parallel and discrete event simulation
VHDL (2nd ed.)
pGVT: an algorithm for accurate GVT estimation
PADS '94 Proceedings of the eighth workshop on Parallel and distributed simulation
Adaptive checkpointing in Time Warp
PADS '94 Proceedings of the eighth workshop on Parallel and distributed simulation
An adaptive memory management protocol for Time Warp parallel simulation
SIGMETRICS '94 Proceedings of the 1994 ACM SIGMETRICS conference on Measurement and modeling of computer systems
Comparative analysis of periodic state saving techniques in time warp simulators
PADS '95 Proceedings of the ninth workshop on Parallel and distributed simulation
Probabilistic adaptive direct optimism control in Time Warp
PADS '95 Proceedings of the ninth workshop on Parallel and distributed simulation
Parameterized Time Warp (PTW): an integrated adaptive solution to optimistic PDES
Journal of Parallel and Distributed Computing
A distributed method to bound rollback lengths for fossil collection in time warp simulators
Information Processing Letters
The Designer's Guide to VHDL
Adaptive Control
Adaptive checkpoint intervals in an optimistically synchronised parallel digital system simulator
VLSI '93 Proceedings of the IFIP TC10/WG 10.5 International Conference on Very Large Scale Integration
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
Software control systems for parallel simulation
Proceedings of the sixteenth workshop on Parallel and distributed simulation
Event pool structures for PDES on many-core Beowulf clusters
Proceedings of the 2013 ACM SIGSIM conference on Principles of advanced discrete simulation
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Several optimizations to the Time Warp synchronization protocol for parallel discrete event simulation have been proposed and studied. Many of these optimizations have included some form of dynamic adjustment (or control) of the operating parameters of the simulation (e.g., checkpoint interval, cancellation strategy). Traditionally dynamic parameter adjustment has been performed at the simulation object level; each simulation object collects measures of its operating behaviors (e.g., rollback frequency, rollback length, etc) and uses them to adjust its operating parameters. The performance data collection functions and parameter adjustment are overhead costs that are incurred in the expectation of higher throughput. This paper presents a method of eliminating some of these overheads through the use of an external object to adjust the control parameters. That is, instead of inserting code for adjusting simulation parameters in the simulation object, an external control object is defined to periodically analyze each simulation object's performance data and revise that object's operating parameters. An implementation of an external control object in the WARPED Time Warp simulation kernel has been completed. The simulation parameters updated by the implemented control system are: checkpoint interval, and cancellation strategy (lazy or aggressive). A comparative analysis of three test cases shows that the external control mechanism provides speedups between 5%-17% over the best performing embedded dynamic adjustment algorithms.