• Login
    View Item 
    •   Home
    • Research
    • Articles
    • View Item
    •   Home
    • Research
    • Articles
    • View Item
    JavaScript is disabled for your browser. Some features of this site may not work without it.

    Browse

    All of KAUSTCommunitiesIssue DateSubmit DateThis CollectionIssue DateSubmit Date

    My Account

    Login

    Quick Links

    Open Access PolicyORCID LibguideTheses and Dissertations LibguideSubmit an Item

    Statistics

    Display statistics

    Unstructured Computational Aerodynamics on Many Integrated Core Architecture

    • CSV
    • RefMan
    • EndNote
    • BibTex
    • RefWorks
    Thumbnail
    Name:
    1-s2.0-S0167819116300564-main.pdf
    Size:
    888.2Kb
    Format:
    PDF
    Description:
    Accepted Manuscript
    Download
    Type
    Article
    Authors
    Al Farhan, Mohammed cc
    Kaushik, Dinesh K.
    Keyes, David E. cc
    KAUST Department
    Applied Mathematics and Computational Science Program
    Computer Science Program
    Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
    Extreme Computing Research Center
    Date
    2016-06-11
    Online Publication Date
    2016-06-11
    Print Publication Date
    2016-11
    Permanent link to this record
    http://hdl.handle.net/10754/613013
    
    Metadata
    Show full item record
    Abstract
    Shared memory parallelization of the flux kernel of PETSc-FUN3D, an unstructured tetrahedral mesh Euler flow code previously studied for distributed memory and multi-core shared memory, is evaluated on up to 61 cores per node and up to 4 threads per core. We explore several thread-level optimizations to improve flux kernel performance on the state-of-the-art many integrated core (MIC) Intel processor Xeon Phi “Knights Corner,” with a focus on strong thread scaling. While the linear algebraic kernel is bottlenecked by memory bandwidth for even modest numbers of cores sharing a common memory, the flux kernel, which arises in the control volume discretization of the conservation law residuals and in the formation of the preconditioner for the Jacobian by finite-differencing the conservation law residuals, is compute-intensive and is known to exploit effectively contemporary multi-core hardware. We extend study of the performance of the flux kernel to the Xeon Phi in three thread affinity modes, namely scatter, compact, and balanced, in both offload and native mode, with and without various code optimizations to improve alignment and reduce cache coherency penalties. Relative to baseline “out-of-the-box” optimized compilation, code restructuring optimizations provide about 3.8x speedup using the offload mode and about 5x speedup using the native mode. Even with these gains for the flux kernel, with respect to execution time the MIC simply achieves par with optimized compilation on a contemporary multi-core Intel CPU, the 16-core Sandy Bridge E5 2670. Nevertheless, the optimizations employed to reduce the data motion and cache coherency protocol penalties of the MIC are expected to be of value for CFD and many other unstructured applications as many-core architecture evolves. We explore large-scale distributed-shared memory performance on the Cray XC40 supercomputer, to demonstrate that optimizations employed on Phi hybridize to this context, where each of thousands of nodes are comprised of two sockets of Intel Xeon Haswell CPUs with 32 cores per node.
    Citation
    Unstructured Computational Aerodynamics on Many Integrated Core Architecture 2016 Parallel Computing
    Sponsors
    The authors are very appreciative of collaborations with Intel Research Laboratories, the Extreme Computing Research Center at KAUST, and Professor Rio Yokota of the Tokyo Institute of Technology. Support in the form of computing resources was provided by the KAUST Supercomputing Laboratory, and KAUST Information Technology Research Division.
    Publisher
    Elsevier BV
    Journal
    Parallel Computing
    DOI
    10.1016/j.parco.2016.06.001
    Additional Links
    http://linkinghub.elsevier.com/retrieve/pii/S0167819116300564
    ae974a485f413a2113503eed53cd6c53
    10.1016/j.parco.2016.06.001
    Scopus Count
    Collections
    Articles; Applied Mathematics and Computational Science Program; Extreme Computing Research Center; Computer Science Program; Computer, Electrical and Mathematical Science and Engineering (CEMSE) Division

    entitlement

     
    DSpace software copyright © 2002-2022  DuraSpace
    Quick Guide | Contact Us | KAUST University Library
    Open Repository is a service hosted by 
    Atmire NV
     

    Export search results

    The export option will allow you to export the current search results of the entered query to a file. Different formats are available for download. To export the items, click on the button corresponding with the preferred download format.

    By default, clicking on the export buttons will result in a download of the allowed maximum amount of items. For anonymous users the allowed maximum amount is 50 search results.

    To select a subset of the search results, click "Selective Export" button and make a selection of the items you want to export. The amount of items that can be exported at once is similarly restricted as the full export.

    After making a selection, click one of the export format buttons. The amount of items that will be exported is indicated in the bubble next to export format.