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    Alleviating the pressure on memory for seismic modeling

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    Type
    Conference Paper
    Authors
    Abdelkhalak, Rached
    Ltaief, Hatem cc
    Etienne, V.
    Akbudak, Kadir
    Tonellot, T.
    Keyes, David E. cc
    KAUST Department
    Extreme Computing Research Center
    Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
    Applied Mathematics and Computational Science Program
    Office of the President
    Date
    2020-06-14
    Permanent link to this record
    http://hdl.handle.net/10754/665407
    
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    Abstract
    This paper describes two methods to improve the performance of a FDTD solver for the first order formulation of the 3D acoustic wave equation. Based on spatial and temporal cache blocking techniques, these methods enable to maximize bandwidth of the memory subsystem, while reducing data traffic in-between the memory hierarchy. On the one hand, the spatial blocking (SB) approach increases data reuse among cores within each iteration of the time integration. On the other hand, the multicore wavefront diamond temporal blocking (MWD-TB) technique further leverages the SB performance by intrinsically reusing freshly cached data solutions across iterations of the time integration. While SB achieves sixfold performance speedup against the naive implementation (without cache blocking), MWD-TB outperforms SB by up to 50\% on a two-socket 16-core Intel Haswell system.
    Citation
    Abdelkhalak, R., Ltaief, H., Etienne, V., Akbudak, K., Tonellot, T., & Keyes, D. (2019). Alleviating the pressure on memory for seismic modeling. Fourth EAGE Workshop on High Performance Computing for Upstream 2019. doi:10.3997/2214-4609.201903281
    Publisher
    EAGE Publications
    Conference/Event name
    4th EAGE Workshop on High Performance Computing for Upstream in the Middle East: HPC Through the 4th Industrial Revolution
    DOI
    10.3997/2214-4609.201903281
    Additional Links
    https://www.earthdoc.org/content/papers/10.3997/2214-4609.201903281
    ae974a485f413a2113503eed53cd6c53
    10.3997/2214-4609.201903281
    Scopus Count
    Collections
    Conference Papers; Applied Mathematics and Computational Science Program; Extreme Computing Research Center; Computer, Electrical and Mathematical Science and Engineering (CEMSE) Division

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