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    Evaluation of autoparallelization toolkits for commodity GPUs

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    Authors
    Williams, David
    Codreanu, Valeriu
    Yang, Po
    Liu, Baoquan
    Dong, Feng
    Yasar, Burhan
    Mahdian, Babak
    Chiarini, Alessandro
    Zhao, Xia
    Roerdink, Jos B.T.M.
    Affiliation
    University of Groningen
    University of Bedfordshire
    RotaSoft Ltd
    ImageMetry
    Super Computing Solutions
    AnSmart
    Issue Date
    2014-12-31
    Subjects
    autoparallelization
    GPU computing
    
    Metadata
    Show full item record
    Other Titles
    Parallel Processing and Applied Mathematics: 10th International Conference, PPAM 2013, Warsaw, Poland, September 8-11, 2013, Revised Selected Papers, Part I
    Abstract
    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 Verlag
    URI
    http://hdl.handle.net/10547/624621
    DOI
    10.1007/978-3-642-55224-3_42
    Additional Links
    https://link.springer.com/chapter/10.1007/978-3-642-55224-3_42
    Type
    Book chapter
    Language
    en
    ISBN
    9783642552236
    ae974a485f413a2113503eed53cd6c53
    10.1007/978-3-642-55224-3_42
    Scopus Count
    Collections
    Computing

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