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International Conference on High-Performance Computing

HiPC 2000: High Performance Computing — HiPC 2000 pp 301–309Cite as

Parallel Sorting Algorithms with Sampling Techniques on Clusters with Processors Running at Different Speeds

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Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 1970))

Abstract

In this paper we use the notion of quantile to implement Parallel Sorting by Regular Sampling (PSRS) on homogeneous clusters and we introduce a new algorithm for in-core parallel sorting integer keys which is based on the sampling technique. The algorithm is devoted to clusters with processors running at different speeds correlated by a multiplicative constant factor. This is a weak definition of non-homogeneous clusters but a first attempt (to our knowledge) in this direction.

The work reported in this paper is supported in part by NSF Grants #MIP 9707125 and #INT 9815742

See our web link at http://www.laria.u-picardie.fr/~cerin/=paladin/ for a bibliography and a review of techniques about parallel sorting

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References

  1. H. Shi and J. Schaeffer, “Parallel sorting by regular sampling,” Journal of Parallel and Distributed Computing, vol. 14, no. 4, pp. 361–372, 1992.

    Article  MATH  Google Scholar 

  2. O. Bonorden, B. Juurlink, I. von Otte, and I. Rieping, “The paderborn university bsp (pub) library-design, implementation and performance,” in 13th International Parallel Processing Symposium and 10th Symposium on Parallel and Distributed Processing, 12-16 April, 1999, San Juan, Puerto Rico, available electronically through IEEE Computer Society, 1999.

    Google Scholar 

  3. N. S. Afonso Ferreira, “A randomized bsp/cgm algorithm for the maximal independent set problem,” Parallel Processing Letters, vol. 9, no. 3, pp. 411–422, 1999.

    Article  MathSciNet  Google Scholar 

  4. C. Cérin and J.-L. Gaudiot, “Algorithms for stable sorting to minimize communications in networks of workstations and their implementations in bsp,” in IEEE Computer Society International Wokshop on Cluster Computing (IWCC’99), pp. 112–120, 1999.

    Google Scholar 

  5. G. Blelloch, C. Leiserson, and B. Maggs, “A Comparison of Sorting Algorithms for the Connection Machine CM-2,” in Proceedings of the ACM Symposium on Parallel Algorithms and Architectures, July 1991.

    Google Scholar 

  6. H. Li and K. C. Sevcik, “Parallel sorting by overpartitioning,” in Proceedings of the 6th Annual Symposium on Parallel Algorithms and Architectures, (New York, NY, USA), pp. 46–56, ACM Press, June 1994.

    Google Scholar 

  7. Helman and JáJá, “Sorting on clusters of SMPs,” Informatica: An International Journal of Computing and Informatics, vol. 23, 1999.

    Google Scholar 

  8. M. Quinn, “Analysis and benchmarking of two parallel sorting algorithms: Hyperquicksort and quickmerge,” BIT, vol. 29, no. 2, pp. 239–250, 1989.

    Article  MATH  Google Scholar 

  9. X. Li, P. Lu, J. Schaeffer, J. Shillington, P. S. Wong, and H. Shi, “On the versatility of parallel sorting by regular sampling,” Parallel Computing, vol. 19, pp. 1079–1103, Oct. 1993.

    Google Scholar 

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Author information

Authors and Affiliations

  1. Université de Picardie Jules Verne, LaRIA, Bat CURI, 5 rue du moulin neuf, 80000, AMIENS, France

    Christophe Cérin

  2. University of Southern California, Electrical Engineering-Systems, 3740 McClintock Ave., 90089-2563, Los Angeles, CA

    Jean Luc Gaudiot

Authors
  1. Christophe Cérin
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  2. Jean Luc Gaudiot
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Editor information

Editors and Affiliations

  1. DAC-UPC,Computer Architecture Department, Technical University of Catalonia, Campus Nord,D6,Jordi Girona,1-3, Barcelona, Spain

    Mateo Valero

  2. Department of EE-Systems Computer Engineering Division, University of Southern California, 3740 McClintok Ave,EEB 200C, 90089-2562, Los Angeles, CA, USA

    Viktor K. Prasanna

  3. Indian Institute of Science, Sir C.V.Raman Avenue, 560012, Bangalore, India

    Sriram Vajapeyam

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© 2000 Springer-Verlag Berlin Heidelberg

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Cérin, C., Gaudiot, J.L. (2000). Parallel Sorting Algorithms with Sampling Techniques on Clusters with Processors Running at Different Speeds. In: Valero, M., Prasanna, V.K., Vajapeyam, S. (eds) High Performance Computing — HiPC 2000. HiPC 2000. Lecture Notes in Computer Science, vol 1970. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-44467-X_27

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  • DOI: https://doi.org/10.1007/3-540-44467-X_27

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-41429-2

  • Online ISBN: 978-3-540-44467-1

  • eBook Packages: Springer Book Archive

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