PEPS: predictive energy-efficient parallel scheduler for multi-core processors

Maghsoud, Zeinab; Noori, Hamid; Mozaffari, Saeed

doi:10.1007/s11227-020-03562-x

Cited by 5 publications

(7 citation statements)

References 29 publications

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“…[Khaleghzadeh et al 2021] propõem um algoritmo para otimizar o tempo de execuc ¸ão e energia de aplicac ¸ões paralelas que executam em plataformas heterogêneas de alto desempenho. [Maghsoud et al 2021] apresentam uma técnica para otimizar o EDP de aplicac ¸ões paralelas. Para tanto, um modelo de predic ¸ão é construído para determinar o número de núcleos e frequência de CPU ideal do processador.…”

Section: Trabalhos Relacionadosunclassified

Otimizando a Execução de Aplicações Paralelas em Ambiente de Nuvem Heterogênea

Lima

Luizelli²,

Rossi³

et al. 2022

Anais Do XXIII Simpósio Em Sistemas Computacionais De Alto Desempenho (SSCAD 2022)

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A computação na nuvem emerge como uma plataforma alternativa para a execução de aplicações de alto desempenho. Simultaneamente, a atualização de nodos computacionais nestes sistemas pode levar a uma heterogeneidade de recursos. Neste sentido, o desafio de executar aplicações paralelas na nuvem não está apenas relacionado a definição do melhor número de threads para a aplicação, mas também, a escolha ideal da arquitetura que irá executar tal aplicação. No entanto, as características de grau de paralelismo e capacidade computacional têm sido pouco exploradas para fazer a alocação de aplicações numa nuvem heterogênea. Portanto, neste artigo, mostramos que ao considerar o grau de paralelismo de uma aplicação e as características do nodo computacional, ganhos significativos de desempenho e consumo de energia podem ser obtidos quando comparado a maneira padrão com que aplicações são escalonadas num ambiente de nuvem heterogênea.

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Section: Trabalhos Relacionadosunclassified

Otimizando a Execução de Aplicações Paralelas em Ambiente de Nuvem Heterogênea

Lima

Luizelli²,

Rossi³

et al. 2022

Anais Do XXIII Simpósio Em Sistemas Computacionais De Alto Desempenho (SSCAD 2022)

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“…The study in [42] explores a predictive energy-efficient parallel scheduler for multicore processors. The paper introduces techniques to achieve work-stealing scheduling based on predictive models to determine the optimal runtime configuration by selecting the number of active cores and corresponding clock frequency of the processor.…”

Section: Related Workmentioning

confidence: 99%

Methodology for Power-Performance Trade-Off Management in Real-Time Embedded Applications

Popović

Jankovic

2022

Electronics

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An increasing number of battery-powered devices that are used outdoors or in mobile systems put emphasis on the power and energy efficiency as a form of trade-off between application performance and system power consumption. However, lack of objective metrics for the evaluation of application performance degradation poses difficulties for managing such trade-offs in real-time applications. The proposed methodology introduces metrics for modeling of application performance and the technique for its control, enabling more efficient power–performance trade-off management. The methodology allows for selective system performance degradation and fine-grained control of system behavior in the power–performance domain by extending the set of operating point parameters controllable through real-time application. The utilization and the effectiveness of the proposed methodology is evaluated in a simulated environment for different scenarios of the application execution, including system operation above the utilization bounds.

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“…This DVFS hardware strategy hinders the overall performance and brings overheads penalties due to the changes of the (F, V). Software solutions come into play to counter this limitation, including task migration, injection of idle cycles and scheduling that balances the load between the processors to enhance overall energy consumption [ 33 ].…”

Section: Survey Of Energy Optimization Approaches In Wsnsmentioning

confidence: 99%

“…Some of them have focused on the DPM technique [ 36 , 47 , 48 , 49 , 50 , 51 , 52 , 53 , 54 ]. The implementation of the DVFS in WSNs is widely applied [ 33 , 55 , 56 , 57 ]. Only few papers combined DPM with DVFS in WSNs such as in [ 35 , 37 ].…”

Section: Survey Of Energy Optimization Approaches In Wsnsmentioning

confidence: 99%

See 1 more Smart Citation

Towards Hybrid Energy-Efficient Power Management in Wireless Sensor Networks

Chéour

Jmal

Khriji

et al. 2021

Sensors

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Wireless Sensor Networks (WSNs) are prone to highly constrained resources, as a result ensuring the proper functioning of the network is a requirement. Therefore, an effective WSN management system has to be integrated for the network efficiency. Our objective is to model, design, and propose a homogeneous WSN hybrid architecture. This work features a dedicated power utilization optimization strategy specifically for WSNs application. It is entitled Hybrid Energy-Efficient Power manager Scheduling (HEEPS). The pillars of this strategy are based on the one hand on time-out Dynamic Power Management (DPM) Intertask and on the other hand on Dynamic Voltage and Frequency Scaling (DVFS). All tasks are scheduled under Global Earliest Deadline First (GEDF) with new scheduling tests to overcome the Dhall effect. To minimize the energy consumption, the HEEPS predicts, defines and models the behavior adapted to each sensor node, as well as the associated energy management mechanism. HEEPS’s performance evaluation and analysis are performed using the STORM simulator. A comparison to the results obtained with the various state of the art approaches is presented. Results show that the power manager proposed effectively schedules tasks to use dynamically the available energy estimated gain up to 50%.

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PEPS: predictive energy-efficient parallel scheduler for multi-core processors

Cited by 5 publications

References 29 publications

Otimizando a Execução de Aplicações Paralelas em Ambiente de Nuvem Heterogênea

Otimizando a Execução de Aplicações Paralelas em Ambiente de Nuvem Heterogênea

Methodology for Power-Performance Trade-Off Management in Real-Time Embedded Applications

Towards Hybrid Energy-Efficient Power Management in Wireless Sensor Networks

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