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    CUDACLAW: A high-performance programmable GPU framework for the solution of hyperbolic PDEs

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    1805.08846v1.pdf
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    Description:
    Preprint
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    Type
    Preprint
    Authors
    Ohannessian, H. Gorune
    Turkiyyah, George
    Ahmadia, Aron
    Ketcheson, David I. cc
    KAUST Department
    Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
    KAUST Supercomputing Laboratory (KSL)
    Applied Mathematics and Computational Science Program
    Date
    2018-05-21
    Permanent link to this record
    http://hdl.handle.net/10754/632531
    
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    Abstract
    We present cudaclaw, a CUDA-based high performance data-parallel framework for the solution of multidimensional hyperbolic partial differential equation (PDE) systems, equations describing wave motion. cudaclaw allows computational scientists to solve such systems on GPUs without being burdened by the need to write CUDA code, worry about thread and block details, data layout, and data movement between the different levels of the memory hierarchy. The user defines the set of PDEs to be solved via a CUDA- independent serial Riemann solver and the framework takes care of orchestrating the computations and data transfers to maximize arithmetic throughput. cudaclaw treats the different spatial dimensions separately to allow suitable block sizes and dimensions to be used in the different directions, and includes a number of optimizations to minimize access to global memory.
    Publisher
    arXiv
    arXiv
    1805.08846
    Additional Links
    http://arxiv.org/abs/1805.08846v1
    http://arxiv.org/pdf/1805.08846v1
    Collections
    Preprints; Applied Mathematics and Computational Science Program; KAUST Supercomputing Laboratory (KSL); Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division

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