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    Performance Benchmarking of Fast Multipole Methods

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    Name:
    Noha Thesis.pdf
    Size:
    1.530Mb
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    PDF
    Description:
    Noha Thesis Approval Form
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    Type
    Thesis
    Authors
    Al-Harthi, Noha A.
    Advisors
    Keyes, David E. cc
    Committee members
    Bagci, Hakan cc
    Ravasi, Timothy cc
    Program
    Computer Science
    KAUST Department
    Computer, Electrical and Mathematical Science and Engineering (CEMSE) Division
    Date
    2013-06
    Embargo End Date
    2014-06-12
    Permanent link to this record
    http://hdl.handle.net/10754/293890
    
    Metadata
    Show full item record
    Access Restrictions
    At the time of archiving, the student author of this thesis opted to temporarily restrict access to it. The full text of this thesis became available to the public after the expiration of the embargo on 2014-06-12.
    Abstract
    The current trends in computer architecture are shifting towards smaller byte/flop ratios, while available parallelism is increasing at all levels of granularity – vector length, core count, and MPI process. Intel’s Xeon Phi coprocessor, NVIDIA’s Kepler GPU, and IBM’s BlueGene/Q all have a Byte/flop ratio close to 0.2, which makes it very difficult for most algorithms to extract a high percentage of the theoretical peak flop/s from these architectures. Popular algorithms in scientific computing such as FFT are continuously evolving to keep up with this trend in hardware. In the meantime it is also necessary to invest in novel algorithms that are more suitable for computer architectures of the future. The fast multipole method (FMM) was originally developed as a fast algorithm for ap- proximating the N-body interactions that appear in astrophysics, molecular dynamics, and vortex based fluid dynamics simulations. The FMM possesses have a unique combination of being an efficient O(N) algorithm, while having an operational intensity that is higher than a matrix-matrix multiplication. In fact, the FMM can reduce the requirement of Byte/flop to around 0.01, which means that it will remain compute bound until 2020 even if the cur- rent trend in microprocessors continues. Despite these advantages, there have not been any benchmarks of FMM codes on modern architectures such as Xeon Phi, Kepler, and Blue- Gene/Q. This study aims to provide a comprehensive benchmark of a state of the art FMM code “exaFMM” on the latest architectures, in hopes of providing a useful reference for deciding when the FMM will become useful as the computational engine in a given application code. It may also serve as a warning to certain problem size domains areas where the FMM will exhibit insignificant performance improvements. Such issues depend strongly on the asymptotic constants rather than the asymptotics themselves, and therefore are strongly implementation and hardware dependent. The primary objective of this study is to provide these constants on various computer architectures.
    Citation
    Al-Harthi, N. A. (2013). Performance Benchmarking of Fast Multipole Methods. KAUST Research Repository. https://doi.org/10.25781/KAUST-347V2
    DOI
    10.25781/KAUST-347V2
    ae974a485f413a2113503eed53cd6c53
    10.25781/KAUST-347V2
    Scopus Count
    Collections
    MS Theses; Computer Science Program; Computer, Electrical and Mathematical Science and Engineering (CEMSE) Division

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