liu.seSearch for publications in DiVA
Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • oxford
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Perception-aware power management for mobile games via dynamic resolution scaling
Linköping University, Department of Computer and Information Science, Software and Systems. Linköping University, Faculty of Science & Engineering.
Linköping University, Department of Computer and Information Science, Software and Systems. Linköping University, Faculty of Science & Engineering.
Linköping University, Department of Computer and Information Science, Statistics. Linköping University, Faculty of Science & Engineering.
Linköping University, Department of Computer and Information Science, Software and Systems. Linköping University, Faculty of Science & Engineering.
Show others and affiliations
2015 (English)In: 2015 IEEE/ACM INTERNATIONAL CONFERENCE ON COMPUTER-AIDED DESIGN (ICCAD), IEEE , 2015, p. 613-620Conference paper, Published paper (Refereed)
Abstract [en]

Modern mobile devices provide ultra-high resolutions in their display panels. This imposes ever increasing workload on the GPU leading to high power consumption and shortened battery life. In this paper, we first show that resolution scaling leads to significant power savings. Second, we propose a perception-aware adaptive scheme that sets the resolution during game play. We exploit the fact that game players are often willing to trade quality for longer battery life. Our scheme uses decision theory, where the predicted user perception is combined with a novel asymmetric loss function that encodes users' alterations in their willingness to save power.

Place, publisher, year, edition, pages
IEEE , 2015. p. 613-620
Series
ICCAD-IEEE ACM International Conference on Computer-Aided Design, ISSN 1933-7760
National Category
Computer Sciences
Identifiers
URN: urn:nbn:se:liu:diva-124543DOI: 10.1109/ICCAD.2015.7372626ISI: 000368929600084ISBN: 978-1-4673-8388-2 (print)OAI: oai:DiVA.org:liu-124543DiVA, id: diva2:899647
Conference
Computer-Aided Design (ICCAD), 2015 IEEE/ACM International Conference on 2-6 Nov. 2015 Austin, TX
Available from: 2016-02-02 Created: 2016-02-02 Last updated: 2018-12-07
In thesis
1. System-Level Design of GPU-Based Embedded Systems
Open this publication in new window or tab >>System-Level Design of GPU-Based Embedded Systems
2018 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

Modern embedded systems deploy several hardware accelerators, in a heterogeneous manner, to deliver high-performance computing. Among such devices, graphics processing units (GPUs) have earned a prominent position by virtue of their immense computing power. However, a system design that relies on sheer throughput of GPUs is often incapable of satisfying the strict power- and time-related constraints faced by the embedded systems.

This thesis presents several system-level software techniques to optimize the design of GPU-based embedded systems under various graphics and non-graphics applications. As compared to the conventional application-level optimizations, the system-wide view of our proposed techniques brings about several advantages: First, it allows for fully incorporating the limitations and requirements of the various system parts in the design process. Second, it can unveil optimization opportunities through exposing the information flow between the processing components. Third, the techniques are generally applicable to a wide range of applications with similar characteristics. In addition, multiple system-level techniques can be combined together or with application-level techniques to further improve the performance.

We begin by studying some of the unique attributes of GPU-based embedded systems and discussing several factors that distinguish the design of these systems from that of the conventional high-end GPU-based systems. We then proceed to develop two techniques that address an important challenge in the design of GPU-based embedded systems from different perspectives. The challenge arises from the fact that GPUs require a large amount of workload to be present at runtime in order to deliver a high throughput. However, for some embedded applications, collecting large batches of input data requires an unacceptable waiting time, prompting a trade-off between throughput and latency. We also develop an optimization technique for GPU-based applications to address the memory bottleneck issue by utilizing the GPU L2 cache to shorten data access time. Moreover, in the area of graphics applications, and in particular with a focus on mobile games, we propose a power management scheme to reduce the GPU power consumption by dynamically adjusting the display resolution, while considering the user's visual perception at various resolutions. We also discuss the collective impact of the proposed techniques in tackling the design challenges of emerging complex systems.

The proposed techniques are assessed by real-life experimentations on GPU-based hardware platforms, which demonstrate the superior performance of our approaches as compared to the state-of-the-art techniques.

Place, publisher, year, edition, pages
Linköping: Linköping University Electronic Press, 2018. p. 62
Series
Linköping Studies in Science and Technology. Dissertations, ISSN 0345-7524 ; 1964
Keywords
GPU, GPGPU, embedded system, heterogeneous computing, system-level design
National Category
Embedded Systems
Identifiers
urn:nbn:se:liu:diva-152469 (URN)10.3384/diss.diva-152469 (DOI)9789176851753 (ISBN)
Public defence
2018-12-19, Nobel BL32, B-Huset, Campus Valla, Linköping, 13:15 (English)
Opponent
Supervisors
Funder
CUGS (National Graduate School in Computer Science), 995523
Available from: 2018-12-07 Created: 2018-12-07 Last updated: 2018-12-07Bibliographically approved

Open Access in DiVA

No full text in DiVA

Other links

Publisher's full text

Authority records BETA

Maghazeh, ArianBordoloi, Unmesh D.Villani, MattiasEles, PetruPeng, Zebo

Search in DiVA

By author/editor
Maghazeh, ArianBordoloi, Unmesh D.Villani, MattiasEles, PetruPeng, Zebo
By organisation
Software and SystemsFaculty of Science & EngineeringStatistics
Computer Sciences

Search outside of DiVA

GoogleGoogle Scholar

doi
isbn
urn-nbn

Altmetric score

doi
isbn
urn-nbn
Total: 233 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • oxford
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf