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    Data-driven execution of fast multipole methods

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    Type
    Article
    Authors
    Ltaief, Hatem cc
    Yokota, Rio cc
    KAUST Department
    KAUST Supercomputing Laboratory (KSL)
    Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
    Extreme Computing Research Center
    Date
    2013-10-08
    Online Publication Date
    2013-09-17
    Print Publication Date
    2014-08-10
    Embargo End Date
    2014-10-08
    Permanent link to this record
    http://hdl.handle.net/10754/562978
    
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    Abstract
    Fast multipole methods (FMMs) have O (N) complexity, are compute bound, and require very little synchronization, which makes them a favorable algorithm on next-generation supercomputers. Their most common application is to accelerate N-body problems, but they can also be used to solve boundary integral equations. When the particle distribution is irregular and the tree structure is adaptive, load balancing becomes a non-trivial question. A common strategy for load balancing FMMs is to use the work load from the previous step as weights to statically repartition the next step. The authors discuss in the paper another approach based on data-driven execution to efficiently tackle this challenging load balancing problem. The core idea consists of breaking the most time-consuming stages of the FMMs into smaller tasks. The algorithm can then be represented as a directed acyclic graph where nodes represent tasks and edges represent dependencies among them. The execution of the algorithm is performed by asynchronously scheduling the tasks using the queueing and runtime for kernels runtime environment, in a way such that data dependencies are not violated for numerical correctness purposes. This asynchronous scheduling results in an out-of-order execution. The performance results of the data-driven FMM execution outperform the previous strategy and show linear speedup on a quad-socket quad-core Intel Xeon system.Copyright © 2013 John Wiley & Sons, Ltd. Copyright © 2013 John Wiley & Sons, Ltd.
    Citation
    Ltaief, H., & Yokota, R. (2013). Data-driven execution of fast multipole methods. Concurrency and Computation: Practice and Experience, 26(11), 1935–1946. doi:10.1002/cpe.3132
    Publisher
    Wiley
    Journal
    Concurrency and Computation: Practice and Experience
    DOI
    10.1002/cpe.3132
    arXiv
    1203.0889
    Additional Links
    http://arxiv.org/pdf/1203.0889
    ae974a485f413a2113503eed53cd6c53
    10.1002/cpe.3132
    Scopus Count
    Collections
    Articles; KAUST Supercomputing Laboratory (KSL); Extreme Computing Research Center; Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division

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