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Tytuł artykułu

The comparison of parallel sorting algorithms implemented on different hardware platforms

Treść / Zawartość
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Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
Sorting is a common problem in computer science. There are a lot of well-known sorting algorithms created for sequential execution on a single processor. Recently, many-core and multi-core platforms have enabled the creation of wide parallel algorithms. We have standard processors that consist of multiple cores and hardware accelerators, like the GPU. Graphic cards, with their parallel architecture, provide new opportunities to speed up many algorithms. In this paper, we describe the results from the implementation of a few different parallel sorting algorithms on GPU cards and multi-core processors. Then, a hybrid algorithm will be presented, consisting of parts executed on both platforms (a standard CPU and GPU). In recent literature about the implementation of sorting algorithms in the GPU, a fair comparison between many core and multi-core platforms is lacking. In most cases, these describe the resulting time of sorting algorithm executions on the GPU platform and a single CPU core.
Słowa kluczowe
Wydawca
Czasopismo
Rocznik
Strony
679--691
Opis fizyczny
Bibliogr. 11 poz., rys., wykr.
Twórcy
autor
  • ACC AGH Cyfronet, Krakow, Poland
autor
  • ACC AGH Cyfronet, Krakow, Poland
autor
  • AGH University of Science and Technology, Faculty of Computer Science, Electronics and Telecommunications, ACC AGH Cyfronet, Krakow, Poland
autor
  • AGH University of Science and Technology, Faculty of Computer Science, Electronics and Telecommunications, ACC AGH Cyfronet, Krakow, Poland
Bibliografia
  • [1] Sintorn E., Assarson U.: Fast parallel GPU-sorting using a hybrid algorithm. Journal of Parallel and Distributed Computing, vol. 68, pp. 1381–1388, 2008.
  • [2] Cederman D., Tsigas P.: A practical quick-sort algorithm for graphics processors. Proc. of the 16th annual European Symposium on Algorithms, Heidelberg, pp. 246–258, 2008, Springer-Verlag.
  • [3] Govindaraju N. K., Gray J., Kumar R., Manocha D.: Gputerasort: High performance graphics co-processor sorting for large database management. Proc. of ACM SIGMOD International Conference on Management of Data, Chicago, United States, June 2006.
  • [4] Greß N. K., Zachmann G.: Gpuabisort: Optimal parallel sorting on stream architectures. Proc. of the 20th IEEE International Parallel and Distributed Processing Symposium IPDPS , Heidelberg, 2006.
  • [5] Bilardi G., Nicolau A.: Adaptive bitonic sorting: An optimal parallel algorithm for shared memory machines. Technical report, Ithaca, NY, USA, 1986.
  • [6] Batcher K. E.: Sorting networks and their applications. Proc. of the AFIPS’68, April 30-May 2, pp. 307–314, New York, NY, USA.
  • [7] NVIDIA: NVIDIA CUDA. Compute Unified Device Architecture-Programming Guide. 2007.
  • [8] OpenMP: OpenMP website – www.openmp.org.
  • [9] Peters H., Schulz-Hildebrandt O., Luttenberger N.: A Novel Sorting Algorithm for Many-core Architectures Based on Adaptive Bitonic Sort. Proc. of the 2012 IEEE 26th International Parallel and Distributed Processing Symposium, pp. 227–237, IEEE Computer Society Washington, DC, USA, 2012.
  • [10] Szymczyk M.: Równoległy algorytm typu quicksort. Automatyka, vol. 1, z. 1, pp. 402–408, 1997.
  • [11] Sequential and parallel algorithms –http://www.iti.fhflensburg.de/lang/algorithmen/sortieren/algo.htm
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-851dcd87-68e4-44ee-a68f-26965f8f8bca
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