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  • 1.
    Raase, Sebastian
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), Centre for Research on Embedded Systems (CERES).
    A Dataflow Communications Library for Adapteva's Epiphany2015Report (Other academic)
    Abstract [en]

    Adapteva'€™s Epiphany platform is a scalable low-power manycore architecture. Even though Adapteva provides an ANSI C compatible compiler and runtime as well as a Software Development Kit (eSDK), developing for this platform is not particularly easy.

    At Halmstad University, we are interested in dataflow applications and have developed a suitable communications library (e-commlib) for the Epiphany, which we would like to release under a permissive 2-clause BSD license. Given sufficiently aware compute kernels, e-commlib projects can also be compiled and run in a Linux-pthreads environment, which simplifies both development and (functional) debugging. This Technical Report shall document both e-commlib (version 3) and our surrounding infrastructure.

  • 2.
    Raase, Sebastian
    et al.
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), Centre for Research on Embedded Systems (CERES).
    Nordström, Tomas
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), Centre for Research on Embedded Systems (CERES).
    On the Use of a Many-core Processor for Computational Fluid Dynamics Simulations2015In: Procedia Computer Science, ISSN 1877-0509, E-ISSN 1877-0509, Vol. 51, p. 1403-1412Article in journal (Refereed)
    Abstract [en]

    The increased availability of modern embedded many-core architectures supporting floating-point operations in hardware makes them interesting targets in traditional high performance computing areas as well. In this paper, the Lattice Boltzmann Method (LBM) from the domain of Computational Fluid Dynamics (CFD) is evaluated on Adapteva’s Epiphany many-core architecture. Although the LBM implementation shows very good scalability and high floating-point efficiency in the lattice computations, current Epiphany hardware does not provide adequate amounts of either local memory or external memory bandwidth to provide a good foundation for simulation of the large problems commonly encountered in real CFD applications.

  • 3.
    Savas, Süleyman
    et al.
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), Centre for Research on Embedded Systems (CERES).
    Raase, Sebastian
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), Centre for Research on Embedded Systems (CERES).
    Gebrewahid, Essayas
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), Centre for Research on Embedded Systems (CERES).
    Ul-Abdin, Zain
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), Centre for Research on Embedded Systems (CERES).
    Nordström, Tomas
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), Centre for Research on Embedded Systems (CERES).
    Dataflow Implementation of QR Decomposition on a Manycore2016In: MES '16: Proceedings of the Third ACM International Workshop on Many-core Embedded Systems, New York, NY: ACM Press, 2016, p. 26-30Conference paper (Refereed)
    Abstract [en]

    While parallel computer architectures have become mainstream, application development on them is still challenging. There is a need for new tools, languages and programming models. Additionally, there is a lack of knowledge about the performance of parallel approaches of basic but important operations, such as the QR decomposition of a matrix, on current commercial manycore architectures.

    This paper evaluates a high level dataflow language (CAL), a source-to-source compiler (Cal2Many) and three QR decomposition algorithms (Givens Rotations, Householder and Gram-Schmidt). The algorithms are implemented both in CAL and hand-optimized C languages, executed on Adapteva's Epiphany manycore architecture and evaluated with respect to performance, scalability and development effort.

    The performance of the CAL (generated C) implementations gets as good as 2\% slower than the hand-written versions. They require an average of 25\% fewer lines of source code without significantly increasing the binary size. Development effort is reduced and debugging is significantly simplified. The implementations executed on Epiphany cores outperform the GNU scientific library on the host ARM processor of the Parallella board by up to 30x. © 2016 Copyright held by the owner/author(s).

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