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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...
The spatial scale, runtime speed and behavioral detail of epidemic outbreak simulations together require the use of large-scale parallel processing. In this paper, an optimistic parallel discrete event execution of a reaction-diffusion simulation model of epidemic outbreaks is presented, with an implementation over the ??sik simulator. Rollback support is achieved with the development of a novel reversible...
Multi-core processors are commonly available now, but most traditional computer architectural simulators still use single-thread execution. In this paper we use parallel discrete event simulation (PDES) to speedup a cycle-accurate event-driven many-core processor simulator. Evaluation against the sequential version shows that the parallelized one achieves an average speedup of 10.9x (up to 13.6x)...
We propose a computing technique for efficient parallel simulation of compute-intensive DEVS models on the IBM Cell processor, combining multi-grained parallelism and various optimizations to speed up the event execution. Unlike most existing parallelization strategies, our approach explicitly exploits the massive fine-grained event-level parallelism inherent in the simulation process, while most...
Stream processing is an important emerging computational model for performing complex operations on and across multi-source, high volume, unpredictable dataflows. We present Flow, a platform for parallel and distributed stream processing system simulation that provides a flexible modeling environment for analyzing stream processing applications. The Flow stream processing system simulator is a high...
Predicting the time-performance of a Distributed Simulation (DS) system may be of interest to evaluate system alternatives during the development cycle, before the system is implemented. In this paper, we introduce a methodology to predict the execution time of a DS system during its design phase. The methodology is based on a model-building approach that, basing on the design documents of the DS...
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