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Applicability of using internal GPGPUs in industrial control systems
ABB Corporate Research, Västerås, Sweden .
ABB Corporate Research, Västerås, Sweden .
Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.ORCID iD: 0000-0001-6132-7945
ABB AB, Ludvika, Sweden.
2014 (English)In: 19th IEEE International Conference on Emerging Technologies and Factory Automation, ETFA 2014, 2014, Article number 7005096- p.Conference paper, Published paper (Refereed)
Abstract [en]

Industrial control systems are continuously increasing in functionality, connectivity, and levels of integration, and as a consequence they require more computational power. At the same time, these systems have specific requirements related to cost, reliability, timeliness, and thermal power dissipation, which put restrictions on the hardware and software used. Today the high-end embedded CPUs not only provide multiple cores, but also integrated graphics processors (GPU) at close to no additional cost. The use of GPUs for general processing have several potential values in industrial control systems; 1) the added computational power and the high parallelism could pave way for new functionality and 2) the integrated GPU could potentially replace other hardware and thereby reduce the overall cost. In this paper we investigate the applicability of using integrated GPUs in industrial control systems. We do this by evaluating the performance of GPUs with respect to computational problem types and sizes typically found in industrial control systems. In the end we conclude that GPUs are no obvious match for industrial control systems and that several hurdles remain before a wide adoption can be motivated. 

Place, publisher, year, edition, pages
2014. Article number 7005096- p.
Keyword [en]
GPGPU, industrial control, real-time, Control systems, Costs, Factory automation, Hardware, Software reliability, Computational power, Computational problem, Hardware and software, Industrial control systems, Industrial controls, Integrated graphics, Real time, Program processors
National Category
Computer and Information Science Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
URN: urn:nbn:se:mdh:diva-27935DOI: 10.1109/ETFA.2014.7005096ISI: 000360999100047Scopus ID: 2-s2.0-84928024915ISBN: 9781479948468 (print)OAI: oai:DiVA.org:mdh-27935DiVA: diva2:809152
Conference
19th IEEE International Conference on Emerging Technologies and Factory Automation, ETFA 2014, 16 September 2014 through 19 September 2014
Available from: 2015-04-30 Created: 2015-04-30 Last updated: 2016-09-01Bibliographically approved

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Nolte, Thomas

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CiteExportLink to record
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