Результаты поиска по 'products':
Найдено статей: 103
  1. Gadzhiev R.I.
    Estimation of probabilistic model of employee labor process
    Computer Research and Modeling, 2012, v. 4, no. 4, pp. 969-975

    The mathematical estimation model for employee labor process, built on the basis of Bayesian network is presented in the article. The great attention is given to the estimation of qualitative characteristics of labor product. Usage of described model is supposed in the companies with the management employee workflows system.

    Keywords: estimation of labor, workflows modeling, Bayesian network, probabilistic modeling.
    Views (last year): 1.
  2. Reed R.G., Cox M.A., Wrigley T., Mellado B.
    A CPU benchmarking characterization of ARM based processors
    Computer Research and Modeling, 2015, v. 7, no. 3, pp. 581-586

    Big science projects are producing data at ever increases rates. Typical techniques involve storing the data to disk, after minor filtering, and then processing it in large computer farms. Data production has reached a point where on-line processing is required in order to filter the data down to manageable sizes. A potential solution involves using low-cost, low-power ARM processors in large arrays to provide massive parallelisation for data stream computing (DSC). The main advantage in using System on Chips (SoCs) is inherent in its design philosophy. SoCs are primarily used in mobile devices and hence consume less power while maintaining relatively good performance. A benchmarking characterisation of three different models of ARM processors will be presented.

    Keywords: High data throughput, Computing, Big Data, ARM System on Chips, Benchmarking.
    Views (last year): 1.
  3. Sukhoroslov O.V., Rubtsov A.O., Volkov S.Yu.
    Development of distributed computing applications and services with Everest cloud platform
    Computer Research and Modeling, 2015, v. 7, no. 3, pp. 593-599

    The use of service-oriented approach in scientific domains can increase research productivity by enabling sharing, publication and reuse of computing applications, as well as automation of scientific workflows. Everest is a cloud platform that enables researchers with minimal skills to publish and use scientific applications as services. In contrast to existing solutions, Everest executes applications on external resources attached by users, implements flexible binding of resources to applications and supports programmatic access to the platform's functionality. The paper presents current state of the platform, recent developments and remaining challenges.

    Keywords: distributed computing, cloud platform, web services, REST, integration of computing resources, application composition.
    Views (last year): 6. Citations: 2 (RSCI).
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