Результаты поиска по 'distributed data processing':
Найдено статей: 52
  1. Kazymov A.I., Kotov V.M., Mineev M.A., Russakovich N.A., Yakovlev A.V.
    Using CERN cloud technologies for the further ATLAS TDAQ software development and for its application for the remote sensing data processing in the space monitoring tasks
    Computer Research and Modeling, 2015, v. 7, no. 3, pp. 683-689

    The CERN cloud technologies (the CernVM project) give a new possibility for the software developers. The participation of the JINR ATLAS TDAQ working group in the software development for distributed data acquisition and processing system (TDAQ) of the ATLAS experiment (CERN) involves the work in the condition of the dynamically developing system and its infrastructure. The CERN cloud technologies, especially CernVM, provide the most effective access as to the TDAQ software as to the third-part software used in ATLAS. The access to the Scientific Linux environment is provided by CernVM virtual machines and the access software repository — by CernVM-FS. The problem of the functioning of the TDAQ middleware in the CernVM environment was studied in this work. The CernVM usage is illustrated on three examples: the development of the packages Event Dump and Webemon, and the adaptation of the data quality auto checking system of the ATLAS TDAQ (Data Quality Monitoring Framework) for the radar data assessment.

    Keywords: Cloud technologies, virtual machines, remote sensing data processing, ATLAS TDAQ, middleware.
    Views (last year): 2.
  2. Ustimenko O.V.
    Features DIRAC data management
    Computer Research and Modeling, 2015, v. 7, no. 3, pp. 741-744

    The report presents an analysis of Big Data storage solutions in different directions. The purpose of this paper is to introduce the technology of Big Data storage, prospects of storage technologies, for example, the software DIRAC. The DIRAC is a software framework for distributed computing.

    The report considers popular storage technologies and lists their limitations. The main problems are the storage of large data, the lack of quality in the processing, scalability, the lack of rapid availability, the lack of implementation of intelligent data retrieval.

    Experimental computing tasks demand a wide range of requirements in terms of CPU usage, data access or memory consumption and unstable profile of resource use for a certain period. The DIRAC Data Management System (DMS), together with the DIRAC Storage Management System (SMS) provides the necessary functionality to execute and control all the activities related with data.

    Keywords: Distributed storage systems, Big Data, software framework, Data transfer service, Data Management System.
    Views (last year): 2.
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