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Communications of the ACM
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Optimal memory management for time warp parallel simulation
ACM Transactions on Modeling and Computer Simulation (TOMACS) - Special issue on parallel and distributed systems performance
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ANSS '91 Proceedings of the 24th annual symposium on Simulation
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WSC '88 Proceedings of the 20th conference on Winter 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
Memory management techniques for Time Warp on a distributed memory machine
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PADS '95 Proceedings of the ninth workshop on Parallel and distributed simulation
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PADS '95 Proceedings of the ninth workshop on Parallel and distributed simulation
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PADS '96 Proceedings of the tenth workshop on Parallel and distributed simulation
Adaptive memory management and optimism control in time warp
ACM Transactions on Modeling and Computer Simulation (TOMACS)
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WSC '96 Proceedings of the 28th conference on Winter simulation
ROSS: a high-performance, low memory, modular time warp system
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ACM Transactions on Modeling and Computer Simulation (TOMACS)
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Proceedings of the 27th international ACM conference on International conference on supercomputing
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This work presents results from an experimental evaluation of the space-time tradeoffs in Time Warp augmented with the cancelback protocol for memory management. An implementation of the cancelback protocol on Time Warp is described that executes on a shared memory multiprocessor, a 32 processor Kendall Square Research Machine (KSR1). The implementation supports canceling back more than one object when memory has been exhausted. The limited memory performance of the system is evaluated for three different workloads with varying degrees of symmetry. These workloads provide interesting stress cases for evaluating limited memory behavior. We, however, make certain simplifying assumptions (e.g., uniform memory requirement by all the events in the system) to keep the experiments tractable. The experiments are extensively monitored to determine the extent to which various overheads affect performance. It is observed that (i) depending on the available memory and asymmetry in the workload, canceling back several (called the salvage parameter) events at one time may improve performance significantly, by reducing certain overheads, (ii) a performance nearly equivalent to that with unlimited memory can be achieved with only a modest amount of memory depending on the degree of asymmetry in the workload.