research-article

Contention Aware Energy Efficient Scheduling on Heterogeneous Multiprocessors

Authors:

Jagpreet Singh,

Bhargav Mangipudi,

Nitin AuluckAuthors Info & Claims

IEEE Transactions on Parallel and Distributed Systems, Volume 26, Issue 5

Pages 1251 - 1264

https://doi.org/10.1109/TPDS.2014.2322354

Published: 01 May 2015 Publication History

Abstract

Energy efficiency along with enhanced performance are two important goals of scheduling on multiprocessors. This paper proposes a Contention-aware, Energy Efficient, Duplication based Mixed Integer Programming (CEEDMIP) formulation for scheduling task graphs on heterogeneous multiprocessors, interconnected in a distributed system or a network on chip architecture. The effect of duplication is studied with respect to minimizing: the makespan, the total energy for processing tasks and messages on processors and network resources respectively and the tardiness of tasks with respect to their deadlines. Optimizing the use of duplication with MIP provides both energy efficiency and performance by reducing the communication energy consumption and the communication latency. The contention awareness gives a more accurate estimation of the energy consumption. We also propose a corner case that allows the scheduling of a parent task copy after a copy of the child task which may lead to efficient schedules. It has been observed that the proposed MIP with a clustering based heuristic provides scalability and gives 10-30 percent improvement in energy with improved makespan and accuracy when compared with other duplication based energy aware algorithms.

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Cited By

Tang QZhu LLian JZhou LWei J(2020)An efficient multi-functional duplication-based scheduling framework for multiprocessor systemsThe Journal of Supercomputing10.1007/s11227-020-03208-y76:11(9142-9167)Online publication date: 1-Nov-2020
https://dl.acm.org/doi/10.1007/s11227-020-03208-y
Saroja SRevathi T(2020)Hybrid dual-objective parallel genetic algorithm for heterogeneous multiprocessor schedulingCluster Computing10.1007/s10586-019-02934-023:2(441-450)Online publication date: 1-Jun-2020
https://dl.acm.org/doi/10.1007/s10586-019-02934-0
Subbaraj SThiagarajan RRengaraj M(2020)Multi-objective league championship algorithm for real-time task schedulingNeural Computing and Applications10.1007/s00521-018-3950-y32:9(5093-5104)Online publication date: 1-May-2020
https://dl.acm.org/doi/10.1007/s00521-018-3950-y
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cover image IEEE Transactions on Parallel and Distributed Systems

IEEE Transactions on Parallel and Distributed Systems Volume 26, Issue 5

May 2015

291 pages

ISSN:1045-9219

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Copyright © 2014.

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IEEE Press

Publication History

Published: 01 May 2015

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Cited By

Tang QZhu LLian JZhou LWei J(2020)An efficient multi-functional duplication-based scheduling framework for multiprocessor systemsThe Journal of Supercomputing10.1007/s11227-020-03208-y76:11(9142-9167)Online publication date: 1-Nov-2020
https://dl.acm.org/doi/10.1007/s11227-020-03208-y
Saroja SRevathi T(2020)Hybrid dual-objective parallel genetic algorithm for heterogeneous multiprocessor schedulingCluster Computing10.1007/s10586-019-02934-023:2(441-450)Online publication date: 1-Jun-2020
https://dl.acm.org/doi/10.1007/s10586-019-02934-0
Subbaraj SThiagarajan RRengaraj M(2020)Multi-objective league championship algorithm for real-time task schedulingNeural Computing and Applications10.1007/s00521-018-3950-y32:9(5093-5104)Online publication date: 1-May-2020
https://dl.acm.org/doi/10.1007/s00521-018-3950-y
Wang ZXiong NWang HCheng LZhao W(2019)Whole procedure heterogeneous multiprocessors low-power optimization at algorithm-levelCluster Computing10.1007/s10586-018-1920-x22:1(2407-2423)Online publication date: 1-Jan-2019
https://dl.acm.org/doi/10.1007/s10586-018-1920-x
Xie GZeng GXiao XLi RLi K(2017)Energy-Efficient Scheduling Algorithms for Real-Time Parallel Applications on Heterogeneous Distributed Embedded SystemsIEEE Transactions on Parallel and Distributed Systems10.1109/TPDS.2017.273087628:12(3426-3442)Online publication date: 9-Nov-2017
https://dl.acm.org/doi/10.1109/TPDS.2017.2730876

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