A data-traffic aware dynamic power management for general-purpose graphics processing units

Lih Yih Chiou, Chao Kai Yang, Che Pin Chang

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

Abstract

General-purpose graphics processing units (GPGPUs) are gaining popularity. Applications like machine learning and artificial intelligence have been growing rapidly. When hardware complexity increases to meet the computing requirements of the applications, the power efficiency of the hardware becomes an important issue. In this paper, we propose an adaptive power management scheme for GPGPU to enhance power efficiency by proactively detecting the internal activities during runtime and dynamically adjusting the operating frequencies of selected components. The simulation results indicate that, when compared with the baseline approach, the proposed scheme can reduce power consumption by up to 15% with a performance overhead of less than 5% on average.

Original languageEnglish
Title of host publication2019 IEEE International Symposium on Circuits and Systems, ISCAS 2019 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781728103976
DOIs
Publication statusPublished - 2019 Jan 1
Event2019 IEEE International Symposium on Circuits and Systems, ISCAS 2019 - Sapporo, Japan
Duration: 2019 May 262019 May 29

Publication series

NameProceedings - IEEE International Symposium on Circuits and Systems
Volume2019-May
ISSN (Print)0271-4310

Conference

Conference2019 IEEE International Symposium on Circuits and Systems, ISCAS 2019
CountryJapan
CitySapporo
Period19-05-2619-05-29

All Science Journal Classification (ASJC) codes

  • Electrical and Electronic Engineering

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