Efficient aggregation of multiple PLs in distributed memory parallel simulations

Nicol, David M.; Michael, C. C.; Inouye, P.

doi:10.1145/76738.76825

Cited by 29 publications

(3 citation statements)

References 4 publications

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“…Several threads are concurrently executed at runtime. In order to synchronize target simulation time among threads, YAWNS (yet another windowing network simulator) protocol is used [4]. This is a conservative parallel simulation protocol.…”

Section: Related Workmentioning

confidence: 99%

NSIM: An Interconnection Network Simulator for Extreme-Scale Parallel Computers

Miwa

Susukita

Shibamura

et al. 2011

IEICE Trans. Inf. & Syst.

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SUMMARYIn the near future, interconnection networks of massively parallel computer systems will connect more than a hundred thousands of computing nodes. The performance evaluation of the interconnection networks can provide real insights to help the development of efficient communication library. Hence, to evaluate the performance of such interconnection networks, simulation tools capable of modeling the networks with sufficient details, supporting a user-friendly interface to describe communication patterns, providing the users with enough performance information, completing simulations within a reasonable time, are a real necessity. This paper introduces a novel interconnection network simulator NSIM, for the evaluation of the performance of extreme-scale interconnection networks. The simulator implements a simplified simulation model so as to run faster without any loss of accuracy. Unlike the existing simulators, NSIM is built on the execution-driven simulation approach. The simulator also provides a MPI-compatible programming interface. Thus, the simulator can emulate parallel program execution and correctly simulate point-to-point and collective communications that are dynamically changed by network congestion. The experimental results in this paper showed sufficient accuracy of this simulator by comparing the simulator and the real machine. We also confirmed that the simulator is capable of evaluating ultra large-scale interconnection networks, consumes smaller memory area, and runs faster than the existing simulator. This paper also introduces a simulation service built on a cloud environment. Without installing NSIM, users can simulate interconnection networks with various configurations by using a web browser.

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Section: Related Workmentioning

confidence: 99%

NSIM: An Interconnection Network Simulator for Extreme-Scale Parallel Computers

Miwa

Susukita

Shibamura

et al. 2011

IEICE Trans. Inf. & Syst.

View full text Add to dashboard Cite

show abstract

“…The simulations were conducted on the YAWNS (Yet Another Windowing Network Simulator) parallel simulation testbed [20,26], implemented on the Intel family of multiprocessors. We present data from runs executed on the Intel iPSC/860, and upon the Intel Touchstone Delta [15], a largescale multiprocessor also based on Intel's i860 CPU.…”

Section: Empirical Studymentioning

confidence: 99%

Automated Parallelization of Timed Petri-Net Simulations

Nicol

Mao

1995

Journal of Parallel and Distributed Computing

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“…Correctness of the simulation is ensured by the ability of such systems to restore a previous (consistent) simulation state, from which to restart the execution of events. This way of dealing with causality violations has been shown to be quite independent of the lookahead of the simulation, network latency, and other parameters of the model with respect to other optimistic synchronization protocols such as Nicol et al (1989), making it a fervent research field even after more than 30 years from its initial proposal.…”

Section: Introductionmentioning

confidence: 99%

Optimizing Simulation on Shared-Memory Platforms: The Smart Cities Case

Ianni

Marotta

Cingolani

et al. 2018

2018 Winter Simulation Conference (WSC)

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Modern advancements in computing architectures have been accompanied by new emergent paradigms to run Parallel Discrete Event Simulation models efficiently. Indeed, many new paradigms to effectively use the available underlying hardware have been proposed in the literature. Among these, the Share-Everything paradigm tackles massively-parallel shared-memory machines, in order to support speculative simulation by taking into account the limits and benefits related to this family of architectures. Previous results have shown how this paradigm outperforms traditional speculative strategies (such as data-separated Time Warp systems) whenever the granularity of executed events is small. In this paper, we show performance implications of this simulation-engine organization when the simulation models have a variable granularity. To this end, we have selected a traffic model, tailored for smart cities-oriented simulation. Our assessment illustrates the effects of the various tuning parameters related to the approach, opening to a higher understanding of this innovative paradigm.

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Efficient aggregation of multiple PLs in distributed memory parallel simulations

Cited by 29 publications

References 4 publications

NSIM: An Interconnection Network Simulator for Extreme-Scale Parallel Computers

NSIM: An Interconnection Network Simulator for Extreme-Scale Parallel Computers

Automated Parallelization of Timed Petri-Net Simulations

Optimizing Simulation on Shared-Memory Platforms: The Smart Cities Case

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