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    Parallel MLEM on multicore architectures

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    Authors
    Kustner, Tilman
    Weidendorfer, Josef
    Schirmer, Jasmine
    Klug, Tobias
    Trinitis, Carsten
    Ziegler, Sybille
    Affiliation
    Technische Universität München
    Issue Date
    2009
    Subjects
    sparse matrix-vector multiplication
    maximum likelihood expectation maximization
    
    Metadata
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    Abstract
    The efficient use of multicore architectures for sparse matrix-vector multiplication (SpMV) is currently an open challenge. One algorithm which makes use of SpMV is the maximum likelihood expectation maximization (MLEM) algorithm. When using MLEM for positron emission tomography (PET) image reconstruction, one requires a particularly large matrix. We present a new storage scheme for this type of matrix which cuts the memory requirements by half, compared to the widely-used compressed sparse row format. For parallelization we combine the two partitioning techniques recursive bisection and striping. Our results show good load balancing and cache behavior. We also give speedup measurements on various modern multicore systems.
    Citation
    Küstner, T., Weidendorfer, J., Schirmer, J., Klug, T., Trinitis, C., Ziegler, S. (2009) 'Parallel MLEM on Multicore Architectures' in ICCS '09 Proceedings of the 9th International Conference on Computational Science: Part I: 491-500
    Publisher
    Springer
    URI
    http://hdl.handle.net/10547/272038
    DOI
    10.1007/978-3-642-01970-8_48
    Additional Links
    http://dl.acm.org/citation.cfm?id=1561015.1560813
    Type
    Conference papers, meetings and proceedings
    Language
    en
    ISBN
    978-3-642-01969-2
    ae974a485f413a2113503eed53cd6c53
    10.1007/978-3-642-01970-8_48
    Scopus Count
    Collections
    Centre for Research in Distributed Technologies (CREDIT)

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