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Downsampling Algorithms for Large Sparse Matrices

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21240%2F15%3A00218582" target="_blank" >RIV/68407700:21240/15:00218582 - isvavai.cz</a>

  • Result on the web

    <a href="http://link.springer.com/article/10.1007%2Fs10766-014-0315-8#" target="_blank" >http://link.springer.com/article/10.1007%2Fs10766-014-0315-8#</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1007/s10766-014-0315-8" target="_blank" >10.1007/s10766-014-0315-8</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    Downsampling Algorithms for Large Sparse Matrices

  • Original language description

    Mapping of sparse matrices to processors of a parallel system may have a significant impact on the development of sparse-matrix algorithms and, in effect, to their efficiency. We present and empirically compare two downsampling algorithms for sparse matrices. The first algorithm is independent of particular matrix-processors mapping, while the second one is adapted for cases where matrices are partitioned among processors according to contiguous chunks of rows/columns. We show that the price for the versatility of the first algorithm is the collective communication performed by all processors. The second algorithm uses more efficient communication strategy, which stems from the knowledge of mapping of matrices to processors, and effectively outperformsthe first algorithm in terms of running time.

  • Czech name

  • Czech description

Classification

  • Type

    J<sub>x</sub> - Unclassified - Peer-reviewed scientific article (Jimp, Jsc and Jost)

  • CEP classification

    IN - Informatics

  • OECD FORD branch

Result continuities

  • Project

    <a href="/en/project/GAP202%2F12%2F2011" target="_blank" >GAP202/12/2011: Parallel Input/Output Algorithms for Very Large Sparse Matrices</a><br>

  • Continuities

    P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Others

  • Publication year

    2015

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Data specific for result type

  • Name of the periodical

    International Journal of Parallel Programming

  • ISSN

    0885-7458

  • e-ISSN

  • Volume of the periodical

    43

  • Issue of the periodical within the volume

    5

  • Country of publishing house

    US - UNITED STATES

  • Number of pages

    24

  • Pages from-to

    679-702

  • UT code for WoS article

    000358648600001

  • EID of the result in the Scopus database

    2-s2.0-84938963170