Repast HPC with Optimistic Time Management

Görür, Bilge Kaan; İmre, Kayhan M.; Oğuztüzün, Halit; Yılmaz, Levent

doi:10.22360/springsim.2016.hpc.046

Cited by 4 publications

(2 citation statements)

References 22 publications

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“…The only option is to go massively parallel due to availability of cheap parallel local hardware with many cores, or cloud services like Amazon EC. This trend has been already recognised in the field of ABS as a research challenge for Large-scale ABMS (Macal 2016) was called out and as a substantial body of research for parallel ABS shows Logan and Theodoropoulos 2001;Lees et al 2008;Riley et al 2003;Gasser and Kakugawa 2002;Himmelspach and Uhrmacher 2007;Minson and Theodoropoulos 2008;Gorur et al 2016;Hay and Wilsey 2015;Abar et al 2017;Cicirelli et al 2015).…”

Section: Introductionmentioning

confidence: 99%

“…In addition, various distributed simulation environments for ABS have been developed and their internals published in research papers: the SPADES system (Riley et al 2003) manages agents through UNIX pipes using a parallel sense-think-act cycle employing a conservative PDES approach; Mace3J (Gasser and Kakugawa 2002) a Java based system running on single-or multicore workstations implements a message passing approach to parallelism; James II (Himmelspach and Uhrmacher 2007) is also a Java based system and focuses on PDEVS simulation with a plugin architecture to facilitate reuse of models; the well known RePast-HPC (Minson and Theodoropoulos 2008;Gorur et al 2016) framework is using a PDES engine under the hood.…”

Section: Introductionmentioning

confidence: 99%

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A tale of lock-free agents: towards Software Transactional Memory in parallel Agent-Based Simulation

Thaler

Siebers

2019

Complex Adapt Syst Model

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With the decline of Moore's law and the ever increasing availability of cheap massively parallel hardware, it becomes more and more important to embrace parallel programming methods to implement Agent-Based Simulations (ABS). This has been acknowledged in the field a while ago and numerous research on distributed parallel ABS exists, focusing primarily on Parallel Discrete Event Simulation as the underlying mechanism. However, these concepts and tools are inherently difficult to master and apply and often an excess in case implementers simply want to parallelise their own, custom agent-based model implementation. However, with the established programming languages in the field, Python, Java and C++, it is not easy to address the complexities of parallel programming due to unrestricted side effects and the intricacies of low-level locking semantics. Therefore, in this paper we propose the use of a lock-free approach to parallel ABS using Software Transactional Memory (STM) in conjunction with the pure functional programming language Haskell, which in combination, removes some of the problems and complexities of parallel implementations in imperative approaches. We present two case studies, in which we compare the performance of lock-based and lock-free STM implementations in two different well known Agent-Based Models, where we investigate both the scaling performance under increasing number of CPU cores and the scaling performance under increasing number of agents. We show that the lock-free STM implementations consistently outperform the lock-based ones and scale much better to increasing number of CPU cores both on local hardware and on Amazon EC. Further, by utilizing the pure functional language Haskell we gain the benefits of immutable data and lack of unrestricted side effects guaranteed at compile-time, making validation easier and leading to increased confidence in the correctness of an implementation, something of fundamental importance and benefit in parallel programming in general and scientific computing like ABS in particular.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

A tale of lock-free agents: towards Software Transactional Memory in parallel Agent-Based Simulation

Thaler

Siebers

2019

Complex Adapt Syst Model

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Predetermined Rollbacks: An extension to Time Warp for spatially parallel agent-based simulation

Görür

İmre

Oğuztüzün

et al. 2019

Simulation Modelling Practice and Theory

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Fidelity and Performance of State Fast-forwarding in Microscopic Traffic Simulations

Andelfinger

Xu²,

Eckhoff

et al. 2020

ACM Trans. Model. Comput. Simul.

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Common car-following models for microscopic traffic simulation assume a time advancement using fixed-sized time steps. However, a purely time-driven execution is inefficient when the states of some agents are independent of other agents and thus predictable far into the simulated future. We propose a method to accelerate microscopic traffic simulations based on identifying independence among agent state updates. Instead of iteratively updating an agent’s state throughout a sequence of time steps, a computationally inexpensive “fast-forward” function advances the agent’s state to the time of its earliest possible interaction with other agents. We present an algorithm to determine independence intervals in microscopic traffic simulations and derive fast-forward functions for several well-known traffic models. In contrast to existing approaches based on reducing the level of detail, our approach retains the microscopic nature of the simulation. An evaluation is performed for a synthetic scenario and on the road network of Singapore. At low traffic densities, maximum speedup factors of about 2.6 and 1.6 are achieved, while at the highest considered densities, only few opportunities for fast-forwarding exist. We show that the deviation from purely time-driven execution is reduced to a minimum when choosing an adequate numerical integration scheme to execute the time-driven updates. Verification results show that the overall deviation in vehicle travel times is marginal.

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Repast HPC with Optimistic Time Management

Cited by 4 publications

References 22 publications

A tale of lock-free agents: towards Software Transactional Memory in parallel Agent-Based Simulation

A tale of lock-free agents: towards Software Transactional Memory in parallel Agent-Based Simulation

Predetermined Rollbacks: An extension to Time Warp for spatially parallel agent-based simulation

Fidelity and Performance of State Fast-forwarding in Microscopic Traffic Simulations

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