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Analysing Metric Data Structures Thinking of an Efficient GPU Implementation

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IAENG Transactions on Engineering Technologies

Part of the book series: Lecture Notes in Electrical Engineering ((LNEE,volume 229))

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Abstract

Similarity search is becoming a field of interest because it can be applied to different areas in science and engineering. In real applications, when large volumes of data are processing, query response time can be quite high. In this case, it is necessary to apply mechanisms to significantly reduce the average query response time. For that purpose, modern GPU/Multi-GPU systems offer a very impressive cost/performance ratio. In this paper, the authors make a comparative study of the most popular pivot selection methods in order to stablish a set of attractive features from the point of view of future GPU implementations.

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Acknowledgments

This work has been supported by the Ministerio de Ciencia e Innovación, project SATSIM (Ref: CGL2010-20787-C02-02), Spain and Research Center, University of Magallanes, Chile. Also, this work has been partially supported by CAPAP-H3 Network (TIN2010-12011-E).

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Authors and Affiliations

  1. Computer Engineering Department, University of Magallanes, Avenida Bulnes, 01855, Punta Arenas, Chile

    Roberto Uribe-Paredes

  2. Computing Systems Department, University of Castilla-La Mancha, Ave. Espaa s/n, 020071, Albacete, Spain

    Enrique Arias, Diego Cazorla & José Luis Sánchez

Authors
  1. Roberto Uribe-Paredes
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  2. Enrique Arias
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  3. Diego Cazorla
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  4. José Luis Sánchez
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Corresponding author

Correspondence to Roberto Uribe-Paredes .

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Editors and Affiliations

  1. , Department of Multimedia Engineering, Mokpo National University, Dorim-ri, MuanGun 61, Chonnam, 534-729, Korea, Republic of (South Korea)

    Gi-Chul Yang

  2. IAENG Secretariat, Hung To Road, Unit 1, 1/F 37-39, Hong Kong, Hong Kong SAR

    Sio-long Ao

  3. School of Engineering, Applied Mathematics and Computing, Cranfield University, College Road, Cranfield, MK43 0AL, Bedfordshire, United Kingdom

    Len Gelman

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Uribe-Paredes, R., Arias, E., Cazorla, D., Luis Sánchez, J. (2013). Analysing Metric Data Structures Thinking of an Efficient GPU Implementation. In: Yang, GC., Ao, Sl., Gelman, L. (eds) IAENG Transactions on Engineering Technologies. Lecture Notes in Electrical Engineering, vol 229. Springer, Dordrecht. https://doi.org/10.1007/978-94-007-6190-2_7

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  • DOI: https://doi.org/10.1007/978-94-007-6190-2_7

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  • Publisher Name: Springer, Dordrecht

  • Print ISBN: 978-94-007-6189-6

  • Online ISBN: 978-94-007-6190-2

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