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Perception-aware power management for mobile games via dynamic resolution scaling
Linköpings universitet, Institutionen för datavetenskap, Programvara och system. Linköpings universitet, Tekniska fakulteten.
Linköpings universitet, Institutionen för datavetenskap, Programvara och system. Linköpings universitet, Tekniska fakulteten.
Linköpings universitet, Institutionen för datavetenskap, Statistik. Linköpings universitet, Tekniska fakulteten.
Linköpings universitet, Institutionen för datavetenskap, Programvara och system. Linköpings universitet, Tekniska fakulteten.
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2015 (Engelska)Ingår i: 2015 IEEE/ACM INTERNATIONAL CONFERENCE ON COMPUTER-AIDED DESIGN (ICCAD), IEEE , 2015, s. 613-620Konferensbidrag, Publicerat paper (Refereegranskat)
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.

Ort, förlag, år, upplaga, sidor
IEEE , 2015. s. 613-620
Serie
ICCAD-IEEE ACM International Conference on Computer-Aided Design, ISSN 1933-7760
Nationell ämneskategori
Datavetenskap (datalogi)
Identifikatorer
URN: urn:nbn:se:liu:diva-124543DOI: 10.1109/ICCAD.2015.7372626ISI: 000368929600084ISBN: 978-1-4673-8388-2 (tryckt)OAI: oai:DiVA.org:liu-124543DiVA, id: diva2:899647
Konferens
Computer-Aided Design (ICCAD), 2015 IEEE/ACM International Conference on 2-6 Nov. 2015 Austin, TX
Tillgänglig från: 2016-02-02 Skapad: 2016-02-02 Senast uppdaterad: 2018-12-07
Ingår i avhandling
1. System-Level Design of GPU-Based Embedded Systems
Öppna denna publikation i ny flik eller fönster >>System-Level Design of GPU-Based Embedded Systems
2018 (Engelska)Doktorsavhandling, sammanläggning (Övrigt vetenskapligt)
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.

Ort, förlag, år, upplaga, sidor
Linköping: Linköping University Electronic Press, 2018. s. 62
Serie
Linköping Studies in Science and Technology. Dissertations, ISSN 0345-7524 ; 1964
Nyckelord
GPU, GPGPU, embedded system, heterogeneous computing, system-level design
Nationell ämneskategori
Inbäddad systemteknik
Identifikatorer
urn:nbn:se:liu:diva-152469 (URN)10.3384/diss.diva-152469 (DOI)9789176851753 (ISBN)
Disputation
2018-12-19, Nobel BL32, B-Huset, Campus Valla, Linköping, 13:15 (Engelska)
Opponent
Handledare
Forskningsfinansiär
CUGS (National Graduate School in Computer Science), 995523
Tillgänglig från: 2018-12-07 Skapad: 2018-12-07 Senast uppdaterad: 2019-09-30Bibliografiskt granskad

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