Результаты поиска по 'discretization':
Найдено статей: 93
  1. Smirnov S.A., Tarasov A.S.
    An automated system for program parameters fine tuning in the cloud
    Computer Research and Modeling, 2015, v. 7, no. 3, pp. 587-592

    The paper presents a software system aimed at finding best (in some sense) parameters of an algorithm. The system handles both discrete and continuous parameters and employs massive parallelism offered by public clouds. The paper presents an overview of the system, a method to measure algorithm's performance in the cloud and numerical results of system's use on several problem sets.

    Keywords: algorithmic parameter optimization, parameter tuning, cloud computing.
  2. Lemtyuzhnikova D.V.
    Parallel representation of local elimination algorithm for accelerating the solving sparse discrete optimization problems
    Computer Research and Modeling, 2015, v. 7, no. 3, pp. 699-705

    The decomposition algorithms provide approaches to deal with NP-hardness in solving discrete optimization problems (DOPs). In this article one of the promising ways to exploit sparse matrices — local elimination algorithm in parallel interpretation (LEAP) are demonstrated. That is a graph-based structural decomposition algorithm, which allows to compute a solution in stages such that each of them uses results from previous stages. At the same time LEAP heavily depends on elimination ordering which actually provides solving stages. Also paper considers tree- and block-parallel for LEAP and required realization process of it comparison of a several heuristics for obtaining a better elimination order and shows how is related graph structure, elimination ordering and solving time.

    Keywords: discrete optimization, volunteer computing, local elimination algorithm, parallel computing, sparse problems, elimination tree.
    Views (last year): 1.
  3. Smirnov S.A., Voloshinov V.V.
    Pre-decomposition of discrete optimization problems to speed up the branch and bound method in a distributed computing environment
    Computer Research and Modeling, 2015, v. 7, no. 3, pp. 719-725

    The paper presents an implementation of branch and bound algorithm employing coarse grained parallelism. The system is based on CBC (COIN-OR branch and cut) open-source MIP solver and inter-process communication capabilities of Erlang. Numerical results show noticeable speedup in comparison to single-threaded CBC instance.

    Keywords: branch and bound algorithm, coarse grained parallelism.
    Views (last year): 2. Citations: 2 (RSCI).
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