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Implementing I/O-efficient Data Structures Using TPIE

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Algorithms — ESA 2002 (ESA 2002)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 2461))

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Abstract

In recent years, many theoretically I/O-efficient algorithms and data structures have been developed. The TPIE project at Duke University was started to investigate the practical importance of these theoretical results. The goal of this ongoing project is to provide a portable, extensible, flexible, and easy to use C++ programming environment for efficiently implementing I/O-algorithms and data structures. The TPIE library has been developed in two phases. The first phase focused on supporting algorithms with a sequential I/O pattern, while the recently developed second phase has focused on supporting on-line I/O-efficient data structures, which exhibit a more random I/O pattern. This paper describes the design and implementation of the second phase of TPIE.

Supported in part by the National Science Foundation through ESS grant EIA- 9870734, RI grant EIA-9972879, CAREER grant CCR-9984099, ITR grant EIA- 0112849, and U.S.-Germany Cooperative Research Program grant INT-0129182.

Supported in part by the National Science Foundation through ESS grant EIA- 9870734 and RI grant EIA-9972879.

Supported in part by the National Science Foundation through research grants CCR-9877133 and EIA-9870734 and by the Army Research Office through MURI grant DAAH04-96-1-0013.

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References

  1. P.K. Agarwal, L. Arge, and S. Govindarajan. CRB-tree: An optimal indexing scheme for 2d aggregate queries. Manuscript, 2002.

    Google Scholar 

  2. P.K. Agarwal, L. Arge, O. Procopiuc, and J. S. Vitter. A framework for index bulk loading and dynamization. In Proc. 28th Intl. Colloq. Automata, Languages and Programming (ICALP), 2001.

    Google Scholar 

  3. A. Aggarwal and J. S. Vitter. The Input/Output complexity of sorting and related problems. Communications of the ACM, 31(9):1116–1127, 1988.

    Article  MathSciNet  Google Scholar 

  4. L. Arge. External memory data structures. In J. Abello, P.M. Pardalos, and M.G.C. Resende, editors, Handbook of Massive Data Sets, pages 313–358. Kluwer Academic Publishers, 2002.

    Google Scholar 

  5. L. Arge, A. Danner, and S.-M. Teh. I/O-efficient point location using persistent B-trees. Manuscript, 2002.

    Google Scholar 

  6. L. Arge, K. H. Hinrichs, J. Vahrenhold, and J. S. Vitter. Efficient bulk operations on dynamic R-trees. Algorithmica, 33(1):104–128, 2002.

    Article  MATH  MathSciNet  Google Scholar 

  7. L. Arge, O. Procopiuc, S. Ramaswamy, T. Suel, J. Vahrenhold, and J. S. Vitter. A unified approach for indexed and non-indexed spatial joins. In Proc. Conference on Extending Database Technology, pages 413–429, 1999.

    Google Scholar 

  8. L.A. Arge and J. Vahrenhold. I/O-efficient dynamic planar point location. In Proc. ACM Symp. Computational Geometry, 2000.

    Google Scholar 

  9. B. Becker, S. Gschwind, T. Ohler, B. Seeger, and P. Widmayer. An asymptotically optimal multiversion B-tree. VLDB Journal, 5(4):264–275, 1996.

    Article  Google Scholar 

  10. N. Beckmann, H.-P. Kriegel, R. Schneider, and B. Seeger. The R*-tree: An efficient and robust access method for points and rectangles. In Proc. SIGMOD Intl. Conf. on Management of Data, pages 322–331, 1990.

    Google Scholar 

  11. J. L. Bentley. Multidimensional binary search trees used for associative searching. Commun. ACM, 18(9):509–517, Sept. 1975.

    Article  MATH  MathSciNet  Google Scholar 

  12. D. Comer. The ubiquitous B-tree. ACM Comput. Surv., 11:121–137, 1979.

    Article  MATH  Google Scholar 

  13. A. Crauser and K. Mehlhorn. LEDA-SM: Extending LEDA to secondary memory. In Proc. Workshop on Algorithm Engineering, 1999.

    Google Scholar 

  14. S. Huddleston and K. Mehlhorn. A new data structure for representing sorted lists. Acta Informatica, 17:157–184, 1982.

    Article  MATH  MathSciNet  Google Scholar 

  15. K. Mehlhorn and S. Näher. LEDA: A Platform for Combinatorial and Geometric Computing. Cambridge University Press, Cambridge, UK, 2000.

    Google Scholar 

  16. M.H. Overmars. The Design of Dynamic Data Structures, volume 156 of Lecture Notes Comput. Sci. Springer-Verlag, Heidelberg, West Germany, 1983.

    Google Scholar 

  17. O. Procopiuc, P.K. Agarwal, L. Arge, and J. S. Vitter. Bkd-tree: A dynamic scalable kd-tree. Manuscript, 2002.

    Google Scholar 

  18. J.T. Robinson. The K-D-B-tree: A search structure for large multidimensional dynamic indexes. In Proc. SIGMOD Intl. Conf. on Management of Data, pages 10–18, 1981.

    Google Scholar 

  19. D.E. Vengro. and J. S. Vitter. Supporting I/O-efficient scientific computation in TPIE. In Proc. IEEE Symp. on Parallel and Distributed Computing, pages 74–77, 1995.

    Google Scholar 

  20. J. S. Vitter. External memory algorithms and data structures: Dealing with MASSIVE data. ACM Computing Surveys, 33(2):209–271, 2001.

    Article  Google Scholar 

  21. J. S. Vitter and E.A. M. Shriver. Algorithms for parallel memory, I: Two-level memories. Algorithmica, 12(2–3):110–147, 1994.

    Article  MATH  MathSciNet  Google Scholar 

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Author information

Authors and Affiliations

  1. Department of Computer Science, Duke University, Center for Geometric and Biological Computing, Durham, NC, 27708, USA

    Lars Arge, Octavian Procopiuc & Jeffrey Scott Vitter

Authors
  1. Lars Arge
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  2. Octavian Procopiuc
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  3. Jeffrey Scott Vitter
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Editor information

Editors and Affiliations

  1. Fakultät II: Mathematik und Naturwissenschaften, Technische Universität Berlin, Strasse des 17. Juni 136, 10623, Berlin, Germany

    Rolf Möhring

  2. Department of Mathematics and Computer Science, University of Leicester, University Road, LE1 7RH, Leicester, UK

    Rajeev Raman

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© 2002 Springer-Verlag Berlin Heidelberg

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Arge, L., Procopiuc, O., Scott Vitter, J. (2002). Implementing I/O-efficient Data Structures Using TPIE. In: Möhring, R., Raman, R. (eds) Algorithms — ESA 2002. ESA 2002. Lecture Notes in Computer Science, vol 2461. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45749-6_12

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  • DOI: https://doi.org/10.1007/3-540-45749-6_12

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-44180-9

  • Online ISBN: 978-3-540-45749-7

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