liu.seSök publikationer i DiVA
Ändra sökning
RefereraExporteraLänk till posten
Permanent länk

Direktlänk
Referera
Referensformat
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • oxford
  • Annat format
Fler format
Språk
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Annat språk
Fler språk
Utmatningsformat
  • html
  • text
  • asciidoc
  • rtf
Saving Energy without Defying Deadlines on Mobile GPU-based Heterogeneous Systems
Linköpings universitet, Institutionen för datavetenskap, Programvara och system. Linköpings universitet, Tekniska högskolan.
Linköpings universitet, Institutionen för datavetenskap, Programvara och system. Linköpings universitet, Tekniska högskolan. (ESLAB)
Linköpings universitet, Institutionen för datavetenskap, Programvara och system. Linköpings universitet, Tekniska högskolan. (ESLAB)
Linköpings universitet, Institutionen för datavetenskap, Programvara och system. Linköpings universitet, Tekniska högskolan. (ESLAB)
Visa övriga samt affilieringar
2014 (Engelska)Ingår i: 2014 International Conference on Hardware/Software Codesign and System Synthesis, Association for Computing Machinery (ACM), 2014Konferensbidrag, Publicerat paper (Refereegranskat)
Abstract [en]

With the advent of low-power programmable compute cores based on GPUs, GPU-equipped heterogeneous platforms are becoming common in a wide spectrum of industries including safety-critical domains like the automotive industry. While the suitability of GPUs for throughput oriented applications is well-accepted, their applicability for real-time applications remains an open issue. Moreover, in mobile/embedded systems, energy-efficient computing is a major concern and yet, there has been no systematic study on the energy savings that GPUs may potentially provide. In this paper, we propose an approach to utilize both the GPU and the CPU in a heterogeneous fashion to meet the deadlines of a real-time application while ensuring that we maximize the energy savings. We note that GPUs are inherently built to maximize the throughput and this poses a major challenge when deadlines must be satisfied. The problem becomes more acute when we consider the fact that GPUs are more energy efficient than CPUs and thus, a naive approach that is based on maximizing GPU utilization might easily lead to infeasible solutions from a deadline perspective.

Ort, förlag, år, upplaga, sidor
Association for Computing Machinery (ACM), 2014.
Nationell ämneskategori
Data- och informationsvetenskap
Identifikatorer
URN: urn:nbn:se:liu:diva-112689DOI: 10.1145/2656075.2656097ISBN: 978-1-4503-3051-0 (tryckt)OAI: oai:DiVA.org:liu-112689DiVA, id: diva2:769462
Konferens
International Conference on Hardware/Software Codesign and System Synthesis (CODES+ISSS 2014), New Delhi, India, October 12-17, 2014
Tillgänglig från: 2014-12-08 Skapad: 2014-12-08 Senast uppdaterad: 2018-12-07Bibliografiskt granskad
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

Open Access i DiVA

Fulltext saknas i DiVA

Övriga länkar

Förlagets fulltext

Personposter BETA

Maghazeh, ArianBordoloi, Unmesh D.Horga, AdrianEles, PetruPeng, Zebo

Sök vidare i DiVA

Av författaren/redaktören
Maghazeh, ArianBordoloi, Unmesh D.Horga, AdrianEles, PetruPeng, Zebo
Av organisationen
Programvara och systemTekniska högskolan
Data- och informationsvetenskap

Sök vidare utanför DiVA

GoogleGoogle Scholar

doi
isbn
urn-nbn

Altmetricpoäng

doi
isbn
urn-nbn
Totalt: 277 träffar
RefereraExporteraLänk till posten
Permanent länk

Direktlänk
Referera
Referensformat
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • oxford
  • Annat format
Fler format
Språk
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Annat språk
Fler språk
Utmatningsformat
  • html
  • text
  • asciidoc
  • rtf