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  • 1.
    Sjöström, Oskar
    et al.
    Linköping University, Department of Computer and Information Science, Software and Systems. Linköping University, Faculty of Science & Engineering.
    Ko, Soon Heum
    Linköping University, National Supercomputer Centre (NSC).
    Dastgeer, Usman
    Linköping University, Department of Computer and Information Science, Software and Systems. Linköping University, Faculty of Science & Engineering.
    Li, Lu
    Linköping University, Department of Computer and Information Science, Software and Systems. Linköping University, Faculty of Science & Engineering.
    Kessler, Christoph
    Linköping University, Department of Computer and Information Science, Software and Systems. Linköping University, Faculty of Science & Engineering.
    Portable Parallelization of the EDGE CFD Application for GPU-based Systems using the SkePU Skeleton Programming Library2016In: Parallel Computing: On the Road to Exascale / [ed] Gerhard R. Joubert; Hugh Leather; Mark Parsons; Frans Peters; Mark Sawyer, IOS Press, 2016, p. 135-144Conference paper (Refereed)
    Abstract [en]

    EDGE is a complex application for computational fluid dynamics used e.g. for aerodynamic simulations in avionics industry. In this work we present the portable, high-level parallelization of EDGE for execution on multicore CPU and GPU based systems by using the multi-backend skeleton programming library SkePU. We first expose the challenges of applying portable high-level parallelization to a complex scientific application for a heterogeneous (GPU-based) system using (SkePU) skeletons and discuss the encountered flexibility problems that usually do not show up in skeleton toy programs. We then identify and implement necessary improvements in SkePU to become applicable for applications containing computations on complex data structures and with irregular data access. In particular, we improve the MapArray skeleton and provide a new MultiVector container for operand data that can be used with unstructured grid data structures. Although there is no SkePU skeleton specifically dedicated to handling computations on unstructured grids and its data structures, we still obtain portable speedup of EDGE with both multicore CPU and GPU execution by using the improved MapArray skeleton of SkePU.

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