Improving utility of GPU in accelerating industrial applications with user-centred automatic code translation
Authors
Yang, PoDong, Feng
Codreanu, Valeriu
Williams, David
Roerdink, Jos B.T.M.
Anvari-Moghaddam, Amjad
Min, Geyong
Affiliation
University of BedfordshireLiverpool John Moores University
SURFsara
University of Groningen
Aalborg University
University of Exeter
Issue Date
2017-07-24Subjects
parallel computing
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SMEs, particularly those whose business is focused on developing innovative produces, are limited by a major bottleneck on the speed of computation in many applications. The recent developments in GPUs have been the marked increase in their versatility in many computational areas. But due to the lack of specialist GPU (Graphics processing units) programming skills, the explosion of GPU power has not been fully utilized in general SME applications by inexperienced users. Also, existing automatic CPU-to-GPU code translators are mainly designed for research purposes with poor user interface design and hard-to-use. Little attentions have been paid to the applicability, usability and learnability of these tools for normal users. In this paper, we present an online automated CPU-to-GPU source translation system, (GPSME) for inexperienced users to utilize GPU capability in accelerating general SME applications. This system designs and implements a directive programming model with new kernel generation scheme and memory management hierarchy to optimize its performance. A web service based interface is designed for inexperienced users to easily and flexibly invoke the automatic resource translator. Our experiments with non-expert GPU users in 4 SMEs reflect that GPSME system can efficiently accelerate real-world applications with at least 4x and have a better applicability, usability and learnability than existing automatic CPU-to-GPU source translatorsCitation
Yang P, Dong F, Codreanu V, Williams D, Roerdink JBTM, Anvari-Moghaddam A, Min G (2017) 'improving Utility of GPU in Accelerating Industrial Applications with User-centred Automatic Code Translation', IEEE Transactions on Industrial Informatics, 14 (4), pp.-.Publisher
IEEEAdditional Links
https://ieeexplore.ieee.org/document/7990251/Type
ArticleLanguage
enISSN
1551-3203Sponsors
European Commissionae974a485f413a2113503eed53cd6c53
10.1109/TII.2017.2731362
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