Segment-aware energy-efficient management of heterogeneous memory system for ultra-low-power IoT devices

Hayeon Choi, Youngkyoung Koo, Sangsoo Park

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

4 Scopus citations

Abstract

The emergence of IoT (Internet of Things) has brought various studies on low-power techniques back to embedded systems. In general, minimizing power consumed by program executions is the main consideration of system design. While running programs, executing data-dependent program code results in a large number of memory accesses which consume huge amount of power. Further, most embedded systems consist of multiple types of memory devices, i.e., heterogeneous memory system, to benefit the different characteristics of memory devices. In this paper, we conduct a research on low-power techniques to reduce the power consumption of heterogeneous memory to achieve ultra-low-power in the system level. This study proposes a segment-aware energy-efficient management to improve the power efficiency considering the characteristics and structures of the memory devices. In the proposed approach, the technique migrates program code from allocated memory device to another if the consumed power is considered to be less. We also analyze and evaluate the comprehensive effects on energy efficiency by applying the technique as well. Compared to the unmodified program code, our model reduces power consumption up to 12.98% by migrating functions.

Original languageEnglish
Title of host publication2017 2nd International Multidisciplinary Conference on Computer and Energy Science, SpliTech 2017
EditorsJoel J. P. C. Rodrigues, Sandro Nizetic, Luigi Patrono, Joel J. P. C. Rodrigues, Zeljka Milanovic, Petar Solic, Katarina Vukojevic, Toni Perkovic
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9789532900712
StatePublished - 28 Aug 2017
Event2nd International Multidisciplinary Conference on Computer and Energy Science, SpliTech 2017 - Split, Croatia
Duration: 12 Jul 201714 Jul 2017

Publication series

Name2017 2nd International Multidisciplinary Conference on Computer and Energy Science, SpliTech 2017

Conference

Conference2nd International Multidisciplinary Conference on Computer and Energy Science, SpliTech 2017
Country/TerritoryCroatia
CitySplit
Period12/07/1714/07/17

Bibliographical note

Funding Information:
ACKNOWLEDGMENT This work was supported by the National Research Foundation of Korea funded by the Korean Government (NRF-2014S1A5B6037290)

Publisher Copyright:
© 2017 Univeristy of Split, FESB.

Keywords

  • Heterogeneous memory
  • Internet of Things
  • Power consumption
  • Segment
  • Ultra-Low-Power

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