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Accelerate SOMA Using Parallel Processing in GPGPU

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27240%2F17%3A10238702" target="_blank" >RIV/61989100:27240/17:10238702 - isvavai.cz</a>

  • Alternative codes found

    RIV/61989100:27740/17:10238702

  • Result on the web

    <a href="https://link.springer.com/chapter/10.1007/978-3-319-50904-4_6" target="_blank" >https://link.springer.com/chapter/10.1007/978-3-319-50904-4_6</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1007/978-3-319-50904-4_6" target="_blank" >10.1007/978-3-319-50904-4_6</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    Accelerate SOMA Using Parallel Processing in GPGPU

  • Original language description

    This paper presents methods for implementing SOMA (Self-Organizing Migrating Algorithm) in parallel with the CUDA (Compute Unified Device Architecture) system that can be used to perform the dominant of up-speed when using SOMA algorithm. SOMA has many individual points to find the global minimum which is the key for paralleling this system because each individual can work separately and share the position for all when it moves. Nowadays, due to the humongous size of data and the limitation of the process in single Central Processing Unit (CPU), it becomes impossible to deal with. As a result of these limitations, we need more CPUs working at the same time to do the same job or take advantage of the power of parallel processing in GPGPU (General-Purpose graphics processing unit). Additionally, many supercomputers are built with the need of Parallel Processing in order to meet the power of hardware. Based on the architecture of CUDA, it can handle the threads in SOMA independence. We use two methods with different architecture in CUDA to help SOMA run much faster than single threading method. This paper also uses some techniques to help SOMA work more effective.

  • Czech name

  • Czech description

Classification

  • Type

    D - Article in proceedings

  • CEP classification

  • OECD FORD branch

    10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Result continuities

  • Project

  • Continuities

    S - Specificky vyzkum na vysokych skolach

Others

  • Publication year

    2017

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Data specific for result type

  • Article name in the collection

    Lecture Notes in Electrical Engineering. Volume 465

  • ISBN

    978-3-319-69813-7

  • ISSN

    1876-1100

  • e-ISSN

    1876-1119

  • Number of pages

    10

  • Pages from-to

    53-62

  • Publisher name

    Springer

  • Place of publication

    Cham

  • Event location

    Ho Či Minovo Město

  • Event date

    Dec 7, 2017

  • Type of event by nationality

    WRD - Celosvětová akce

  • UT code for WoS article