A task scheduling algorithm for HPC applications using colored stochastic Petri Net models

Mironescu, Ion Dan; Vintan, Lucian

doi:10.1109/iccp.2017.8117051

Cited by 4 publications

(5 citation statements)

References 21 publications

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“…In this research, we continue and complement our work presented in [20]. The hardware we consider in our approach is a cluster of heterogeneous nodes, implementing a High Performance Computer System (HPC).…”

Section: The Proposed High Performance Computing Systemmentioning

confidence: 90%

“…The proposed load balancing algorithm described in [20] and schematically presented in figure 1 has two levels, corresponding to the software architecture levels. At the CHARM++ level, the load distribution is performed by the chares.…”

Section: Proposed Load Balancermentioning

confidence: 99%

“…The modelling and simulation were performed using the Snoopy tool [9]. Hardware and software components were modelled as described in [20]. Each PU is represented by a token; this token is initially located in the idle place and travels to the other places representing points of the computation reached by the PU.…”

Section: Petri Net Modelmentioning

confidence: 99%

“…The application is composed of the scheduler net, which connects to the StarPU run time net, and the load balancer, which connects to the Charm++ runtime. We re-used the Charm++ structure presented in [20]. Details of the scheduler for one PU are presented in Figure 2.…”

Section: Petri Net Modelmentioning

confidence: 99%

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A Simulation Based Analysis of an Multi Objective Diffusive Load Balancing Algorithm

Mironescu

Vintan

2018

INT J COMPUT COMMUN

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In this paper, we presented a further development of our research on developing an optimal software-hardware mapping framework. We used the Petri Net model of the complete hardware and software High Performance Computing (HPC) system running a Computational Fluid Dynamics (CFD) application, to simulate the behaviour of the proposed diffusive two level multi-objective load-balancing algorithm. We developed an meta-heuristic algorithm for generating an approximation of the Pareto-optimal set to be used as reference. The simulations showed the advantages of this algorithm over other diffusive algorithms: reduced computational and communication overhead and robustness due to low dependence on uncertain data. The algorithm also had the capacity to handle unpredictable events as a load increase due to domain refinement or loss of a computation resource due to malfunction.

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Section: The Proposed High Performance Computing Systemmentioning

confidence: 90%

Section: Proposed Load Balancermentioning

confidence: 99%

Section: Petri Net Modelmentioning

confidence: 99%

Section: Petri Net Modelmentioning

confidence: 99%

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A Simulation Based Analysis of an Multi Objective Diffusive Load Balancing Algorithm

Mironescu

Vintan

2018

INT J COMPUT COMMUN

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“…As a tool to model discrete event systems, Petri nets [13][14][15][16][17][18] have been widely used to model the business process applications, which have shown great power in dealing with concurrences and conflicts. erefore, in this paper, the modeling methodology for collaborative business process towards IoT applications is investigated on the basis of Petri nets.…”

Section: Introductionmentioning

confidence: 99%

Modeling and Optimization for Collaborative Business Process Towards IoT Applications

Cheng

Zhao

Cheng

et al. 2018

Mobile Information Systems

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The rapid development of Internet of Things (IoT) attracts growing attention from both industry and academia. IoT seamlessly connects the real world and cyberspace via various business process applications hosted on the IoT devices, especially on smart sensors. Due to the discrete distribution and complex sensing environment, multiple coordination patterns exist in the heterogeneous sensor networks, making modeling and analysis particularly difficult. In addition, massive sensing events need to be routed, forwarded and processed in the distributed execution environment. Therefore, the corresponding sensing event scheduling algorithm is highly desired. In this paper, we propose a novel modeling methodology and optimization algorithm for collaborative business process towards IoT applications. We initially extend the traditional Petri nets with sensing event factor. Then, the formal modeling specification is investigated and the existing coordination patterns, including event unicasting pattern, event broadcasting pattern, and service collaboration pattern, are defined. Next, we propose an optimization algorithm based on Dynamic Priority First Response (DPFR) to solve the problem of sensing event scheduling. Finally, the approach presented in this paper has been validated to be valid and implemented through an actual development system.

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Formal Techniques for Simulations of Distributed Web System Models

Rak

2021

Advances in Intelligent Systems and Computing

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A task scheduling algorithm for HPC applications using colored stochastic Petri Net models

Cited by 4 publications

References 21 publications

A Simulation Based Analysis of an Multi Objective Diffusive Load Balancing Algorithm

A Simulation Based Analysis of an Multi Objective Diffusive Load Balancing Algorithm

Modeling and Optimization for Collaborative Business Process Towards IoT Applications

Formal Techniques for Simulations of Distributed Web System Models

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