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
Link To Document :
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