Результаты поиска по 'paralleling':
Найдено статей: 94
  1. 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.

    Views (last year): 2. Citations: 2 (RSCI).
  2. Molecular dynamic methods that use ReaxFF force field allow one to obtain sufficiently good results in simulating large multicomponent chemically reactive systems. Here is represented an algorithm of searching optimal parameters of molecular-dynamic force field ReaxFF for arbitrary chemical systems and its implementation. The method is based on the multidimensional technique of global minimum search suggested by R.G. Strongin. It has good scalability useful for running on distributed parallel computers.

    Views (last year): 1. Citations: 1 (RSCI).
  3. Ershov N.M.
    Non-uniform cellular genetic algorithms
    Computer Research and Modeling, 2015, v. 7, no. 3, pp. 775-780

    In this paper, we introduce the concept of non-uniform cellular genetic algorithm, in which a number of parameters that affect the operation of genetic operators is dependent on the location of the cells of a given cellular space. The results of numerical comparison of non-uniform cellular genetic algorithms with the standard genetic algorithms, showing the advantages of the proposed approach while minimizing multimodal functions with a large number of local extrema, are presented. The coarse-grained parallel implementation of the non-uniform algorithms using the technology of MPI is considered.

    Views (last year): 9. Citations: 3 (RSCI).
  4. Ershov N.M., Popova N.N.
    Natural models of parallel computations
    Computer Research and Modeling, 2015, v. 7, no. 3, pp. 781-785

    Course “Natural models of parallel computing”, given for senior students of the Faculty of Computational Mathematics and Cybernetics, Moscow State University, is devoted to the issues of supercomputer implementation of natural computational models and is, in fact, an introduction to the theory of natural computing, a relatively new branch of science, formed at the intersection of mathematics, computer science and natural sciences (especially biology). Topics of the natural computing include both already classic subjects such as cellular automata, and relatively new, introduced in the last 10–20 years, such as swarm intelligence. Despite its biological origin, all these models are widely applied in the fields related to computer data processing. Research in the field of natural computing is closely related to issues and technology of parallel computing. Presentation of theoretical material of the course is accompanied by a consideration of the possible schemes for parallel computing, in the practical part of the course it is supposed to perform by the students a software implementation using MPI technology and numerical experiments to investigate the effectiveness of the chosen schemes of parallel computing.

    Views (last year): 17. Citations: 2 (RSCI).
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