Parallel Computational Reconfiguration Based on a PGAS Model (特集:情報爆発時代におけるIT基盤技術) Parallel Computational Reconfiguration Based on a PGAS Model (preprint)

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Abstract

In order to improve the resource utilization of clusters and supercomputers and thus deliver application results to users faster, it is essential for a job scheduler to expand and shrink parallel computations flexibly. In order to enable the flexible job scheduling, the parallel computations have to be reconfigurable. With this motivation, this paper proposes, implements and evaluates DMI, a global-view-based PGAS framework that enables easy programming of reconfigurable and high-performance parallel iterative computations. DMI provides programming interfaces with which a programmer can program the reconfiguration easily with a global-view. Our performance evaluations showed that DMI can efficiently adapt the parallelism of long-running parallel iterative computations, such as a real-world finite element method and large-scale iterative graph search, to the dynamic increase and decrease of available resources through the reconfiguration.------------------------------ This is a preprint of an article intended for publication Journal of Information Processing(JIP). This preprint should not be cited. This article should be cited as: Journal of Information Processing Vol.20(2012) No.1 (online) DOI http://dx.doi.org/10.2197/ipsjjip.20.140------------------------------In order to improve the resource utilization of clusters and supercomputers and thus deliver application results to users faster, it is essential for a job scheduler to expand and shrink parallel computations flexibly. In order to enable the flexible job scheduling, the parallel computations have to be reconfigurable. With this motivation, this paper proposes, implements and evaluates DMI, a global-view-based PGAS framework that enables easy programming of reconfigurable and high-performance parallel iterative computations. DMI provides programming interfaces with which a programmer can program the reconfiguration easily with a global-view. Our performance evaluations showed that DMI can efficiently adapt the parallelism of long-running parallel iterative computations, such as a real-world finite element method and large-scale iterative graph search, to the dynamic increase and decrease of available resources through the reconfiguration.------------------------------ This is a preprint of an article intended for publication Journal of Information Processing(JIP). This preprint should not be cited. This article should be cited as: Journal of Information Processing Vol.20(2012) No.1 (online) DOI http://dx.doi.org/10.2197/ipsjjip.20.140------------------------------

Journal

  • 情報処理学会論文誌  

    情報処理学会論文誌 52(12), 14p, 2011-12-15 

    情報処理学会

Codes

  • NII Article ID (NAID)
    110008719895
  • NII NACSIS-CAT ID (NCID)
    AN00116647
  • Text Lang
    ENG
  • Article Type
    Journal Article
  • ISSN
    1882-7764
  • NDL Article ID
    023426052
  • NDL Call No.
    YH247-743
  • Data Source
    NDL  IPSJ 
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