Showing 1 - 20 results of 84 for search '"massively parallel computing"', query time: 0.12s Refine Results
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    Parallelization of the NASA Goddard Cumulus Ensemble Model for Massively Parallel Computing by Hann-Ming Henry Juang, Wei-Kuo Tao, Xiping Zeng, Chung-Lin Shie, Stephen Lang, Joanne Simpson

    Published 2007-01-01
    “…Massively parallel computing, using a message passing interface (MPI), has been implemented into a three-dimensional version of the Goddard Cumulus Ensemble (GCE) model. …”
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    Improved Massively Parallel Computation Algorithms for MIS, Matching, and Vertex Cover by Ghaffari, Mohsen, Gouleakis, Themistoklis, Konrad, Christian, Mitrović, Slobodan, Rubinfeld, Ronitt

    Published 2021
    “…We present O(log log n)-round algorithms in the Massively Parallel Computation (MPC) model, with Õ(n) memory per machine, that compute a maximal independent set, a 1 + ε approximation of maximum matching, and a 2 + ε approximation of minimum vertex cover, for any n-vertex graph and any constant ε > 0. …”
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    HTN: a new hierarchical iterconnection network for massively parallel computers by Rahman, M.M. Hafizur, Susumu, Horiguchi

    Published 2003
    “…However, hierarchical interconnection networks provide high performance at low cost by exploring the locality that exists in communication patterns of massively parallel computers. In this paper, we propose a new hierarchical interconnection network, called Hierarchical Torus Network (HTN). …”
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    TTN: a high performance hierarchical interconnection network for massively parallel computers by Rahman, M.M. Hafizur, Inoguchi, Yasushi, Sato, Yukinori, Horiguchi, Susumu

    Published 2009
    “…Interconnection networks play a crucial role in the performance of massively parallel computers. Hierarchical interconnection networks provide high performance at low cost by exploring the locality that exists in the communication patterns of massively parallel computers. …”
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    A statistical method for massive data based on partial least squares algorithm by Xu Yan

    Published 2024-01-01
    “…To solve this application contradiction, a parallel computing strategy based on NVIDIA CU-DA architecture is proposed to implement the partial least squares algorithm using a graphics processor (GPU) with massively parallel computing features as the computing device and combining the advantages of GPU memory. …”
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