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Solutions For Optimizing The Data Parallel Prefix Sum Algorithm Using The Compute Unified Device Architecture

  • Ion Lungu

    ()

    (Academy of Economic Studies Bucharest)

  • Dana-Mihaela Petroşanu

    ()

    (University Politehnica of Bucharest)

  • Alexandru Pîrjan

    ()

    (Romanian-American University Bucharest)

Registered author(s):

    In this paper, we analyze solutions for optimizing the data parallel prefix sum function using the Compute Unified Device Architecture (CUDA) that provides a viable solution for accelerating a broad class of applications. The parallel prefix sum function is an essential building block for many data mining algorithms, and therefore its optimization facilitates the whole data mining process. Finally, we benchmark and evaluate the performance of the optimized parallel prefix sum building block in CUDA.

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    File URL: http://www.rebe.rau.ro/RePEc/rau/jisomg/WI11-2/JISOM-WI11-2-A5.pdf
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    Article provided by Romanian-American University in its journal Journal of Information Systems and Operations Management.

    Volume (Year): 5 (2011)
    Issue (Month): 2.1 (December)
    Pages: 465-477

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    Handle: RePEc:rau:journl:v:5:y:2011:i:2.1:p:465-477
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    1. Alexandru PIRJAN, 2010. "Improving Software Performance in the Compute Unified Device Architecture," Informatica Economica, Academy of Economic Studies - Bucharest, Romania, vol. 14(4), pages 30-47.
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