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A considerable amount of research on parallel discrete event simulation has been conducted over the past few decades. However, most of this research has targeted the parallel simulation infrastructure; focusing on data structures, algorithms, and synchronization methods for parallel simulation kernels. Unfortunately, distributed environments often have high communication latencies that can reduce the potential performance of parallel simulations. Effective partitioning of the concurrent simulation objects of the real world models can have a large impact on the amount of network traffic necessary in the simulation, and consequently the overall performance. This paper presents our studies on profiling the characteristics of simulation models and using the collected data to perform partitioning of the models for concurrent execution. Our benchmarks show that Profile Guided Partitioning can result in dramatic performance gains in the parallel simulations. In some of the models, 5-fold improvements of the run time of the concurrently executed simulations were observed.
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Some Properties of Events Executed in Discrete-Event Simulation Models
The field of computer architecture uses quantitative methods to drive the computer system design process. By quantitatively profiling the run time characteristics of computer programs, the principal processing needs of commonly used programs became well understood and computer architects can focus their design solutions toward those needs. The DESMetrics project is established to follow this quantitative model by profiling the execution of Discrete Event Simulation (DES) models in order to focus optimization efforts within DES execution frameworks (and especially parallel DES engines). In particular, the DESMetrics project is designed to capture the run time characteristics of event execution in DES models. Because DES models tend to have fine grained computational processing requirements, the DESMetrics project focuses on the event dependencies and their exchange between the objects in the simulation. For now, we assume that optimization of the actual event processing is well served by conventional compiler and architecture solutions. Although, as will become clear later in Section 6, the possibility of identifying scheduling blocks of events that could potentially be schedule together can be achieved — at least within a single simulation object.
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- Award ID(s):
- 0915337
- PAR ID:
- 10350981
- Date Published:
- Journal Name:
- ACM SIGSIM Conference on Principles of Advanced Discrete Simulation
- Page Range / eLocation ID:
- 165 to 176
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Conference Paper:
- https://doi.org/10.1145/2901378.2901400
