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Computing Strongly Connected Components in Parallel on CUDA

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216224%3A14330%2F11%3A00049681" target="_blank" >RIV/00216224:14330/11:00049681 - isvavai.cz</a>

  • Result on the web

  • DOI - Digital Object Identifier

Alternative languages

  • Result language

    angličtina

  • Original language name

    Computing Strongly Connected Components in Parallel on CUDA

  • Original language description

    The problem of decomposing a directed graph into its strongly connected components is a fundamental graph problem inherently present in many scientific and commercial applications. In this paper we show how some of the existing parallel algorithms can bereformulated in order to be accelerated by NVIDIA CUDA technology. In particular, we design a new CUDA-aware procedure for pivot selection and we adapt the particular parallel algorithms for CUDA accelerated computation. We also experimentally demonstrate that with a single GTX 480 GPU card we can easily outperform optimal serial CPU implementation -- by an order of magnitude in most cases, 40 times on some sufficiently big instances. This is a particularly interesting result as unlike the serial CPU case, the asymptotic complexity of the parallel algorithms is not optimal.

  • Czech name

  • Czech description

Classification

  • Type

    D - Article in proceedings

  • CEP classification

    IN - Informatics

  • OECD FORD branch

Result continuities

  • Project

    Result was created during the realization of more than one project. More information in the Projects tab.

  • Continuities

    P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>Z - Vyzkumny zamer (s odkazem do CEZ)<br>S - Specificky vyzkum na vysokych skolach

Others

  • Publication year

    2011

  • Confidentiality

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

Data specific for result type

  • Article name in the collection

    Proceedings of 25th IEEE International Parallel & Distributed Processing Symposium

  • ISBN

    978-1-61284-372-8

  • ISSN

    1530-2075

  • e-ISSN

  • Number of pages

    12

  • Pages from-to

    544-555

  • Publisher name

    IEEE Computer Society

  • Place of publication

    Anchorage, AK

  • Event location

    Anchorage, AK

  • Event date

    Jan 1, 2011

  • Type of event by nationality

    CST - Celostátní akce

  • UT code for WoS article