DocumentCode
1792336
Title
Applicability of using internal GPGPUs in industrial control systems
Author
Lindgren, Markus ; Sandstrom, Kristian ; Nolte, Thomas ; Hallmans, Daniel
Author_Institution
ABB Corp. Res., Vasteras, Sweden
fYear
2014
fDate
16-19 Sept. 2014
Firstpage
1
Lastpage
7
Abstract
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.
Keywords
control engineering computing; graphics processing units; industrial control; multiprocessing systems; parallel processing; production engineering computing; high-end embedded CPU; industrial control systems; integrated graphics processors; internal GPGPU applicability; multiple cores; parallelism; Benchmark testing; Graphics processing units; Kernel; Performance evaluation; Process control; Sensors; GPGPU; industrial control; real-time;
fLanguage
English
Publisher
ieee
Conference_Titel
Emerging Technology and Factory Automation (ETFA), 2014 IEEE
Conference_Location
Barcelona
Type
conf
DOI
10.1109/ETFA.2014.7005096
Filename
7005096
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