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Energy-optimal software partitioning in heterogeneous multiprocessor embedded systems

Published: 08 June 2008 Publication History

Abstract

Embedded systems with heterogeneous processors extend the energy/timing trade-off flexibility and provide the opportunity to fine tune resource utilization for particular applications. In this paper, we present a resource model that considers the time and energy costs of run-time mode switching, which considerably improves the accuracy of existing models. Given an application, the software partitioning problem then becomes an optimization over energy cost given deadline constraints, which can be formulate as an integer linear programming (ILP) problem. We apply the resource modeling and software partitioning techniques to a multimodule embedded sensing device, the mPlatform, and present a case study of configuring the platform for a real-time sound source localization application on a stack of MSP430 and ARM7 processor based sensing and processing boards.

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      cover image ACM Conferences
      DAC '08: Proceedings of the 45th annual Design Automation Conference
      June 2008
      993 pages
      ISBN:9781605581156
      DOI:10.1145/1391469
      • General Chair:
      • Limor Fix
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      Published: 08 June 2008

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      Author Tags

      1. energy-aware
      2. multi-processor scheduling
      3. real-time systems

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      • (2023)Warp-Aware Adaptive Energy Efficiency Calibration for Multi-GPU SystemsIEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems10.1109/TCAD.2022.320052842:5(1676-1690)Online publication date: May-2023
      • (2022)Dynamic thread mapping for power-efficient many-core systems under performance constraintsMicroprocessors & Microsystems10.1016/j.micpro.2022.10461493:COnline publication date: 1-Sep-2022
      • (2021)Simulation model for energy consumption and acoustic underwater communication of autonomous underwater vehiclesWMU Journal of Maritime Affairs10.1007/s13437-021-00253-z21:1(89-107)Online publication date: 29-Nov-2021
      • (2020)Low-Complexity Run-time Management of Concurrent Workloads for Energy-Efficient Multi-Core SystemsJournal of Low Power Electronics and Applications10.3390/jlpea1003002510:3(25)Online publication date: 25-Aug-2020
      • (2020)Energy Optimization by Software Prefetching for Task Granularity in GPU-Based Embedded SystemsIEEE Transactions on Industrial Electronics10.1109/TIE.2019.294530867:6(5120-5131)Online publication date: Jun-2020
      • (2020)AdaMD: Adaptive Mapping and DVFS for Energy-Efficient Heterogeneous MulticoresIEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems10.1109/TCAD.2019.293506539:10(2206-2217)Online publication date: Oct-2020
      • (2020)PARMA: Parallelization-Aware Run-Time Management for Energy-Efficient Many-Core SystemsIEEE Transactions on Computers10.1109/TC.2020.297578769:10(1507-1518)Online publication date: 1-Oct-2020
      • (2020)Dynamic Energy and Thermal Management of Multi-core Mobile Platforms: A SurveyIEEE Design & Test10.1109/MDAT.2020.298262937:5(25-33)Online publication date: Oct-2020
      • (2019)A Two-Layer Component-Based Allocation for Embedded Systems with GPUsDesigns10.3390/designs30100063:1(6)Online publication date: 19-Jan-2019
      • (2019)PaperWorkProceedings of the ACM Symposium on Document Engineering 201910.1145/3342558.3345403(1-10)Online publication date: 23-Sep-2019
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