Authors
Williams, DavidCodreanu, Valeriu
Yang, Po
Liu, Baoquan
Dong, Feng
Yasar, Burhan
Mahdian, Babak
Chiarini, Alessandro
Zhao, Xia
Roerdink, Jos B.T.M.
Affiliation
University of GroningenUniversity of Bedfordshire
RotaSoft Ltd
ImageMetry
Super Computing Solutions
AnSmart
Issue Date
2014-12-31
Metadata
Show full item recordOther Titles
Parallel Processing and Applied Mathematics: 10th International Conference, PPAM 2013, Warsaw, Poland, September 8-11, 2013, Revised Selected Papers, Part IAbstract
In this paper we evaluate the performance of the OpenACC and Mint toolkits against C and CUDA implementations of the standard PolyBench test suite. Our analysis reveals that performance is similar in many cases, but that a certain set of code constructs impede the ability of Mint to generate optimal code. We then present some small improvements which we integrate into our own GPSME toolkit (which is derived from Mint) and show that our toolkit now out-performs OpenACC in the majority of tests.Citation
Williams D, Codreanu V, Yang P, Liu B, Dong F, Yasar B, Mahdian B, Chiarini A, Zhao X, Roerdink J (2014) 'Evaluation of autoparallelization toolkits for commodity GPUs', in Wyrzykowski R, Dongarra J, Karczewski K, Waśniewski J (ed(s).). Parallel Processing and Applied Mathematics: 10th International Conference, PPAM 2013, Warsaw, Poland, September 8-11, 2013, Revised Selected Papers, Part I, Springer Verlag pp.447-457.Publisher
Springer VerlagAdditional Links
https://link.springer.com/chapter/10.1007/978-3-642-55224-3_42Type
Book chapterLanguage
enISBN
9783642552236ae974a485f413a2113503eed53cd6c53
10.1007/978-3-642-55224-3_42