Skip to content
University of Maryland LibrariesDigital Repository at the University of Maryland
    • Войти
    Просмотр элемента 
    •   Главная
    • College of Computer, Mathematical & Natural Sciences
    • Computer Science
    • Technical Reports from UMIACS
    • Просмотр элемента
    •   Главная
    • College of Computer, Mathematical & Natural Sciences
    • Computer Science
    • Technical Reports from UMIACS
    • Просмотр элемента
    JavaScript is disabled for your browser. Some features of this site may not work without it.

    An Evaluation of Architectural Alternatives for Rapidly Growing Datasets, Active Disks, Clusters, SMPs

    Thumbnail
    Открыть
    CS-TR-3956.ps (485.1Kb)
    No. of downloads: 284

    Auto-generated copy of CS-TR-3956.ps (222.8Kb)
    No. of downloads: 588

    Дата
    1998-12-08
    Автор
    Uysal, Mustafa
    Acharya, Anurag
    Saltz, Joel
    Metadata
    Показать полную информацию
    Аннотации
    Growth and usage trends for several large datasets indicate that there is a need for architectures that scale the processing power as the dataset increases. In this paper, we evaluate three architectural alternatives for rapidly growing and frequently reprocessed datasets: active disks, clusters, and shared memory multiprocessors (SMPs). The focus of this evaluation is to identify potential bottlenecks in each of the alternative architectures and to determine the performance of these architectures for the applications of interest. We evaluate these architectural alternatives using a detailed simulator and a suite of nine applications. Our results indicate that for most of these applications Active Disk and cluster configurations were able to achieve significantly better performance than SMP configurations. Active Disk configurations were able to match (and in some cases improve upon) the performance of commodity cluster configurations. (Also cross-referenced as UMIACS-TR-98-68)
    URI
    http://hdl.handle.net/1903/980
    Collections
    • Technical Reports from UMIACS
    • Technical Reports of the Computer Science Department

    DRUM is brought to you by the University of Maryland Libraries
    University of Maryland, College Park, MD 20742-7011 (301)314-1328.
    Please send us your comments.
    Web Accessibility
     

     

    Просмотр

    Весь DSpaceСообщества и коллекцииДата публикацииАвторыНазванияТематикаЭта коллекцияДата публикацииАвторыНазванияТематика

    Моя учетная запись

    ВойтиРегистрация
    Pages
    About DRUMAbout Download Statistics

    DRUM is brought to you by the University of Maryland Libraries
    University of Maryland, College Park, MD 20742-7011 (301)314-1328.
    Please send us your comments.
    Web Accessibility