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    Exploring Shared-Memory Optimizations for an Unstructured Mesh CFD Application on Modern Parallel Systems

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    Type
    Conference Paper
    Authors
    Mudigere, Dheevatsa
    Sridharan, Srinivas
    Deshpande, Anand
    Park, Jongsoo
    Heinecke, Alexander
    Smelyanskiy, Mikhail
    Kaul, Bharat
    Dubey, Pradeep
    Kaushik, Dinesh
    Keyes, David E. cc
    KAUST Department
    Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
    Applied Mathematics and Computational Science Program
    Extreme Computing Research Center
    Date
    2015-05
    Permanent link to this record
    http://hdl.handle.net/10754/577110
    
    Metadata
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    Abstract
    In this work, we revisit the 1999 Gordon Bell Prize winning PETSc-FUN3D aerodynamics code, extending it with highly-tuned shared-memory parallelization and detailed performance analysis on modern highly parallel architectures. An unstructured-grid implicit flow solver, which forms the backbone of computational aerodynamics, poses particular challenges due to its large irregular working sets, unstructured memory accesses, and variable/limited amount of parallelism. This code, based on a domain decomposition approach, exposes tradeoffs between the number of threads assigned to each MPI-rank sub domain, and the total number of domains. By applying several algorithm- and architecture-aware optimization techniques for unstructured grids, we show a 6.9X speed-up in performance on a single-node Intel® XeonTM1 E5 2690 v2 processor relative to the out-of-the-box compilation. Our scaling studies on TACC Stampede supercomputer show that our optimizations continue to provide performance benefits over baseline implementation as we scale up to 256 nodes.
    Citation
    Mudigere, D., Sridharan, S., Deshpande, A., Park, J., Heinecke, A., Smelyanskiy, M., … Keyes, D. (2015). Exploring Shared-Memory Optimizations for an Unstructured Mesh CFD Application on Modern Parallel Systems. 2015 IEEE International Parallel and Distributed Processing Symposium. doi:10.1109/ipdps.2015.114
    Publisher
    Institute of Electrical and Electronics Engineers (IEEE)
    Journal
    2015 IEEE International Parallel and Distributed Processing Symposium
    DOI
    10.1109/IPDPS.2015.114
    ae974a485f413a2113503eed53cd6c53
    10.1109/IPDPS.2015.114
    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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