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Hartmut Kaiser

  1. Neutron Star Evolutions using Tabulated Equations of State with a New Execution Model.

    Чт, 05/24/2012 - 15:01 — SomNambul
    Authors: Matthew Anderson, Maciej Brodowicz, Hartmut Kaiser, Bryce Adelstein-Lelbach, Thomas Sterling
    Subjects: and Cluster Computing, Distributed, Parallel
    Abstract

    The addition of nuclear and neutrino physics to general relativistic fluid
    codes allows for a more realistic description of hot nuclear matter in neutron
    star and black hole systems. This additional microphysics requires that each
    processor have access to large tables of data, such as equations of state, and
    in large simulations the memory required to store these tables locally can
    become excessive unless an alternative execution model is used.

  2. An Application Driven Analysis of the ParalleX Execution Model.

    Втр, 09/27/2011 - 15:01 — SomNambul
    Authors: Matthew Anderson, Maciej Brodowicz, Hartmut Kaiser, Thomas Sterling
    Subjects: and Cluster Computing, Distributed, Parallel
    Abstract

    Exascale systems, expected to emerge by the end of the next decade, will
    require the exploitation of billion-way parallelism at multiple hierarchical
    levels in order to achieve the desired sustained performance. The task of
    assessing future machine performance is approached by identifying the factors
    which currently challenge the scalability of parallel applications.

  3. Improving the scalability of parallel N-body applications with an event driven constraint based execution model.

    Втр, 09/27/2011 - 15:01 — SomNambul
    Authors: Chirag Dekate, Matthew Anderson, Maciej Brodowicz, Hartmut Kaiser, Bryce Adelstein-Lelbach, Thomas Sterling
    Subjects: and Cluster Computing, Distributed, Parallel
    Abstract

    The scalability and efficiency of graph applications are significantly
    constrained by conventional systems and their supporting programming models.
    Technology trends like multicore, manycore, and heterogeneous system
    architectures are introducing further challenges and possibilities for emerging
    application domains such as graph applications. This paper explores the space
    of effective parallel execution of ephemeral graphs that are dynamically
    generated using the Barnes-Hut algorithm to exemplify dynamic workloads.

Math-arch

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