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A hybrid framework for application allocation and scheduling in multicore systems with energy harvesting

Published: 20 May 2014 Publication History

Abstract

In this paper, we propose a novel hybrid design-time and run-time framework for allocating and scheduling applications in multi-core embedded systems with solar energy harvesting. Due to limited energy availability at run-time, our framework offloads scheduling complexity to design time by creating energy-efficient schedule templates for varying energy budget levels, which are selected at run-time in a manner that is contingent on the available harvested energy and executed with a lightweight slack reclamation scheme that extracts additional energy savings. Our experimental results show that the proposed framework produces energy-efficient and dependency-aware schedules to execute applications under varying and stringent energy constraints, with 23-40% lower miss rates than in prior works on harvesting energy-aware scheduling.

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  • (2021)Fast and Predictable Non-Volatile Data Memory for Real-Time Embedded SystemsIEEE Transactions on Computers10.1109/TC.2020.298826170:3(359-371)Online publication date: 1-Mar-2021
  • (2019)Efficiently Switchable Context-Aware Dataflow Adaptation Technique for Low-Power Multi-Core Embedded SystemsIEEE Access10.1109/ACCESS.2019.29580457(177974-177987)Online publication date: 2019
  • (2018)Optimization of Fault-Tolerant Mixed-Criticality Multi-Core Systems with Enhanced WCRT AnalysisACM Transactions on Design Automation of Electronic Systems10.1145/327515424:1(1-26)Online publication date: 21-Dec-2018
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  1. A hybrid framework for application allocation and scheduling in multicore systems with energy harvesting

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        cover image ACM Conferences
        GLSVLSI '14: Proceedings of the 24th edition of the great lakes symposium on VLSI
        May 2014
        376 pages
        ISBN:9781450328166
        DOI:10.1145/2591513
        Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

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        Published: 20 May 2014

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        Author Tags

        1. DVTS
        2. energy harvesting
        3. mapping and scheduling

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        GLSVLSI '14
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        GLSVLSI '14: Great Lakes Symposium on VLSI 2014
        May 21 - 23, 2014
        Texas, Houston, USA

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        GLSVLSI '14 Paper Acceptance Rate 49 of 179 submissions, 27%;
        Overall Acceptance Rate 312 of 1,156 submissions, 27%

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        View all
        • (2021)Fast and Predictable Non-Volatile Data Memory for Real-Time Embedded SystemsIEEE Transactions on Computers10.1109/TC.2020.298826170:3(359-371)Online publication date: 1-Mar-2021
        • (2019)Efficiently Switchable Context-Aware Dataflow Adaptation Technique for Low-Power Multi-Core Embedded SystemsIEEE Access10.1109/ACCESS.2019.29580457(177974-177987)Online publication date: 2019
        • (2018)Optimization of Fault-Tolerant Mixed-Criticality Multi-Core Systems with Enhanced WCRT AnalysisACM Transactions on Design Automation of Electronic Systems10.1145/327515424:1(1-26)Online publication date: 21-Dec-2018
        • (2018)Context-aware dataflow adaptation technique for low-power multi-core embedded systemsProceedings of the 55th Annual Design Automation Conference10.1145/3195970.3196015(1-6)Online publication date: 24-Jun-2018
        • (2018)PATH: Performance-Aware Task Scheduling for Energy-Harvesting Nonvolatile ProcessorsIEEE Transactions on Very Large Scale Integration (VLSI) Systems10.1109/TVLSI.2018.282560526:9(1671-1684)Online publication date: Sep-2018
        • (2018)Context-Aware Dataflow Adaptation Technique for Low-Power Multi-Core Embedded Systems2018 55th ACM/ESDA/IEEE Design Automation Conference (DAC)10.1109/DAC.2018.8465771(1-6)Online publication date: Jun-2018
        • (2017)Dynamic Power and Energy Management for Energy Harvesting Nonvolatile Processor SystemsACM Transactions on Embedded Computing Systems10.1145/307757516:4(1-23)Online publication date: 11-May-2017

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