Holistic Energy Management with μprocessor Co-Optimization in Fully Integrated Battery-Less IoTs

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Fully integrating on-chip power management modules and microprocessor into a system-on-a-chip (SoC) provides many benefits including lower cost and higher levels of optimization, especially for battery-less energy harvesting operation. However, previous studies have only focused on optimization of individual module, e.g. power converter. There is a lack of systematic optimization of energy efficiency considering microprocessor, regulator, and harvester. This paper performs a holistic study on power efficiency of the whole energy harvesting system including solar cells, on-chip voltage regulators and microprocessors. An optimal scheduling and operation strategy is proposed for achieving the best efficiency and system level performance while avoiding local minimum as in conventional approach. We show that the minimum energy point is different from conventional approaches without a holistic view of the system. We demonstrated the study and proposed scheme using a battery-less solar energy harvesting system and a 65nm fully integrated test chip with 20% additional energy savings.

Original languageEnglish (US)
Title of host publicationProceedings - 31st IEEE International System on Chip Conference, SOCC 2018
EditorsMircea Stan, Helen Li, Karan Bhatia, Ramalingam Sridhar, Massimo Alioto
PublisherIEEE Computer Society
Pages61-66
Number of pages6
ISBN (Electronic)9781538614907
DOIs
StatePublished - Jan 17 2019
Event31st IEEE International System on Chip Conference, SOCC 2018 - Arlington, United States
Duration: Sep 4 2018Sep 7 2018

Publication series

NameInternational System on Chip Conference
Volume2018-September
ISSN (Print)2164-1676
ISSN (Electronic)2164-1706

Conference

Conference31st IEEE International System on Chip Conference, SOCC 2018
CountryUnited States
CityArlington
Period9/4/189/7/18

Fingerprint

Energy harvesting
Energy management
Microprocessor chips
Voltage regulators
Harvesters
Power converters
Solar energy
Energy efficiency
Solar cells
Energy conservation
Scheduling
Coprocessor
Costs

Keywords

  • Low-power design
  • Multi-domain power/energy management
  • Power/energy/thermal aware architecture design

ASJC Scopus subject areas

  • Hardware and Architecture
  • Control and Systems Engineering
  • Electrical and Electronic Engineering

Cite this

Hester, J. D., Jia, T., & Gu, J. (2019). Holistic Energy Management with μprocessor Co-Optimization in Fully Integrated Battery-Less IoTs. In M. Stan, H. Li, K. Bhatia, R. Sridhar, & M. Alioto (Eds.), Proceedings - 31st IEEE International System on Chip Conference, SOCC 2018 (pp. 61-66). [8618523] (International System on Chip Conference; Vol. 2018-September). IEEE Computer Society. https://doi.org/10.1109/SOCC.2018.8618523
Hester, Josiah David ; Jia, Tianyu ; Gu, Jie. / Holistic Energy Management with μprocessor Co-Optimization in Fully Integrated Battery-Less IoTs. Proceedings - 31st IEEE International System on Chip Conference, SOCC 2018. editor / Mircea Stan ; Helen Li ; Karan Bhatia ; Ramalingam Sridhar ; Massimo Alioto. IEEE Computer Society, 2019. pp. 61-66 (International System on Chip Conference).
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abstract = "Fully integrating on-chip power management modules and microprocessor into a system-on-a-chip (SoC) provides many benefits including lower cost and higher levels of optimization, especially for battery-less energy harvesting operation. However, previous studies have only focused on optimization of individual module, e.g. power converter. There is a lack of systematic optimization of energy efficiency considering microprocessor, regulator, and harvester. This paper performs a holistic study on power efficiency of the whole energy harvesting system including solar cells, on-chip voltage regulators and microprocessors. An optimal scheduling and operation strategy is proposed for achieving the best efficiency and system level performance while avoiding local minimum as in conventional approach. We show that the minimum energy point is different from conventional approaches without a holistic view of the system. We demonstrated the study and proposed scheme using a battery-less solar energy harvesting system and a 65nm fully integrated test chip with 20{\%} additional energy savings.",
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Hester, JD, Jia, T & Gu, J 2019, Holistic Energy Management with μprocessor Co-Optimization in Fully Integrated Battery-Less IoTs. in M Stan, H Li, K Bhatia, R Sridhar & M Alioto (eds), Proceedings - 31st IEEE International System on Chip Conference, SOCC 2018., 8618523, International System on Chip Conference, vol. 2018-September, IEEE Computer Society, pp. 61-66, 31st IEEE International System on Chip Conference, SOCC 2018, Arlington, United States, 9/4/18. https://doi.org/10.1109/SOCC.2018.8618523

Holistic Energy Management with μprocessor Co-Optimization in Fully Integrated Battery-Less IoTs. / Hester, Josiah David; Jia, Tianyu; Gu, Jie.

Proceedings - 31st IEEE International System on Chip Conference, SOCC 2018. ed. / Mircea Stan; Helen Li; Karan Bhatia; Ramalingam Sridhar; Massimo Alioto. IEEE Computer Society, 2019. p. 61-66 8618523 (International System on Chip Conference; Vol. 2018-September).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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N2 - Fully integrating on-chip power management modules and microprocessor into a system-on-a-chip (SoC) provides many benefits including lower cost and higher levels of optimization, especially for battery-less energy harvesting operation. However, previous studies have only focused on optimization of individual module, e.g. power converter. There is a lack of systematic optimization of energy efficiency considering microprocessor, regulator, and harvester. This paper performs a holistic study on power efficiency of the whole energy harvesting system including solar cells, on-chip voltage regulators and microprocessors. An optimal scheduling and operation strategy is proposed for achieving the best efficiency and system level performance while avoiding local minimum as in conventional approach. We show that the minimum energy point is different from conventional approaches without a holistic view of the system. We demonstrated the study and proposed scheme using a battery-less solar energy harvesting system and a 65nm fully integrated test chip with 20% additional energy savings.

AB - Fully integrating on-chip power management modules and microprocessor into a system-on-a-chip (SoC) provides many benefits including lower cost and higher levels of optimization, especially for battery-less energy harvesting operation. However, previous studies have only focused on optimization of individual module, e.g. power converter. There is a lack of systematic optimization of energy efficiency considering microprocessor, regulator, and harvester. This paper performs a holistic study on power efficiency of the whole energy harvesting system including solar cells, on-chip voltage regulators and microprocessors. An optimal scheduling and operation strategy is proposed for achieving the best efficiency and system level performance while avoiding local minimum as in conventional approach. We show that the minimum energy point is different from conventional approaches without a holistic view of the system. We demonstrated the study and proposed scheme using a battery-less solar energy harvesting system and a 65nm fully integrated test chip with 20% additional energy savings.

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Hester JD, Jia T, Gu J. Holistic Energy Management with μprocessor Co-Optimization in Fully Integrated Battery-Less IoTs. In Stan M, Li H, Bhatia K, Sridhar R, Alioto M, editors, Proceedings - 31st IEEE International System on Chip Conference, SOCC 2018. IEEE Computer Society. 2019. p. 61-66. 8618523. (International System on Chip Conference). https://doi.org/10.1109/SOCC.2018.8618523