Processing of Range Query Using SIMD and GPU

  • Pavel Bednář
  • Petr Gajdoš
  • Michal Krátký
  • Peter Chovanec
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 185)


Onedimensional or multidimensional range query is one of the most important query of physical implementation of DBMS. The number of compared items (of a data structure) can be enormous especially for lower selectivity of the range query. The number of compare operations increases for more complex items (or tuples) with the longer length, e.g. words stored in a B-tree. Due to the possibly high number of compare operations executed during the range query processing, we can take into account hardware devices providing a parallel task computation like CPU’s SIMD or GPU. In this paper, we show the performance and scalability of sequential, index, CPU’s SIMD, and GPU variants of the range query algorithm. These results make possible a future integration of these computation devices into a DBMS kernel.


Shared Memory Range Query Global Memory Thread Block Data Chunk 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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  1. 1.
    Bayer, R., McCreight, E.: Organization and Maintenance of Large Ordered Indexes. Acta Informatica 3(1), 173–189 (1972)CrossRefGoogle Scholar
  2. 2.
    Beckmann, N., Kriegel, H.P., Schneider, R., Seeger, B.: The R*-Tree: An Efficient and Robust Access Method for Points and Rectangles. In: Proceedings of the ACM International Conference on Management of Data, SIGMOD 1990 (1990)Google Scholar
  3. 3.
    Beier, F., Kilias, T., Sattler, K.U.: GiST Scan Acceleration using Coprocessors. In: Proceedings of 8th Int. Workshop on Data Management on New Hardware, DaMoN 2012 (2012)Google Scholar
  4. 4.
    Chhugani, J., Nguyen, A.D., Lee, V.W., Macy, W., Hagog, M., Chen, Y.K., Baransi, A., Kumar, S., Dubey, P.: Efficient Implementation of Sorting on Multi-Core SIMD CPU Architecture. Proceedings of the VLDB Endowment 1(2) (2008)Google Scholar
  5. 5.
    Chovanec, P., Krátký, M.: Processing of Multidimensional Range Query Using SIMD Instructions. In: Abd Manaf, A., Sahibuddin, S., Ahmad, R., Mohd Daud, S., El-Qawasmeh, E. (eds.) ICIEIS 2011, Part IV. CCIS, vol. 254, pp. 223–237. Springer, Heidelberg (2011)CrossRefGoogle Scholar
  6. 6.
    Chovanec, P., Krátký, M., Bača, R.: Optimization of Disk Accesses for Multidimensional Range Queries. In: Bringas, P.G., Hameurlain, A., Quirchmayr, G. (eds.) DEXA 2010. LNCS, vol. 6261, pp. 358–367. Springer, Heidelberg (2010)CrossRefGoogle Scholar
  7. 7.
    Farber, R.: CUDA Application Design and Development, 1st edn. Morgan Kaufmann (2011)Google Scholar
  8. 8.
    Freeston, M.: A General Solution of the n-dimensional B-tree Problem. In: Proceedings of the ACM International Conference on Management of Data, SIGMOD 1995. ACM Press (1995)Google Scholar
  9. 9.
    Garcia, V., Debreuve, E., Barlaud, M.: Fast k Nearest Neighbor Search using GPU. In: Computer Vision and Pattern Recognition Workshops, pp. 1–6. IEEE Computer Society (2008)Google Scholar
  10. 10.
    Guttman, A.: R-Trees: A Dynamic Index Structure for Spatial Searching. In: Proceedings of the ACM International Conference on Management of Data (SIGMOD 1984), pp. 47–57. ACM Press (June 1984)Google Scholar
  11. 11.
    Hennessy, J.L., Patterson, D.A.: Computer Architecture: A Quantitative Approach, 4th edn. Morgan Kaufmann (2006)Google Scholar
  12. 12.
    Khronos: Khronos: Opencl (2012),
  13. 13.
    Kirk, D.B., Mei, W., Hwu, W.: Programming Massively Parallel Processors: A Hands-on Approach. Applications of GPU Computing Series. Morgan Kaufmann (2010)Google Scholar
  14. 14.
    Krátký, M., Pokorný, J., Snášel, V.: Implementation of XPath Axes in the Multi-dimensional Approach to Indexing XML Data. In: Lindner, W., Fischer, F., Türker, C., Tzitzikas, Y., Vakali, A.I. (eds.) EDBT 2004. LNCS, vol. 3268, pp. 219–229. Springer, Heidelberg (2004)CrossRefGoogle Scholar
  15. 15.
    Lahdenmäki, T., Leach, M.: Relational Database Index Design and the Optimizers. John Wiley and Sons, New Jersey (2005)CrossRefGoogle Scholar
  16. 16.
    Lightstone, S.S., Teorey, T.J., Nadeau, T.: Physical Database Design: the Database Professional’s Guide. Morgan Kaufmann (2007)Google Scholar
  17. 17.
  18. 18.
  19. 19.
    Samet, H.: Foundations of Multidimensional and Metric Data Structures. Morgan Kaufmann (2006)Google Scholar
  20. 20.
    Servetti, A., Rinotti, A., De Martin, J.: Fast Implementation of the MPEG-4 AAC Main and Low Complexity Decoder. In: Proceedings of Acoustics, Speech, and Signal Processing, ICASSP 2004 (2004)Google Scholar
  21. 21.
    Shahbahrami, A., Juurlink, B., Vassiliadis, S.: Performance Comparison of SIMD Implementations of the Discrete Wavelet Transform. In: Proceedings of Application-Specific Systems, Architecture Processors, ASAP 2005 (2005)Google Scholar
  22. 22.
    Slingerland, N., Smith, A.J.: Multimedia Extensions for General Purpose Microprocessors: A Survey. Technical report CSD-00-1124, University of California at Berkeley (2000)Google Scholar
  23. 23.
    Stonebraker, M., Abadi, D., Batkin, A., Chen, X., Cherniack, M., Ferreira, M., Lau, E., Lin, A., Madden, S.: C-store: A Column Oriented DBMS. In: Proceedings of the International Conference on Very Large Data Bases, VLDB 2005 (2005)Google Scholar
  24. 24.
    Willhalm, T., Popovici, N., Boshmaf, Y., Plattner, H., Zeier, A., Schaffner, J.: SIMD-Scan: Ultra Fast In-Memory Table Scan Using On-Chip Vector Processing Units. Proceedings of the VLDB Endowment 2(1) (2009)Google Scholar
  25. 25.
    Zhou, J., Ross, K.A.: Implementing Database Operations Using SIMD Instructions. In: Proceedings of the ACM International Conference on Management of Data, SIGMOD 2002 (2002)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Pavel Bednář
    • 1
  • Petr Gajdoš
    • 1
  • Michal Krátký
    • 1
  • Peter Chovanec
    • 1
  1. 1.Department of Computer ScienceVŠB – Technical University of OstravaOstravaCzech Republic

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