Nothing Special   »   [go: up one dir, main page]
Skip to main content
Springer Nature Link
Log in

Generic Programming and High-Performance Libraries

  • Published:
International Journal of Parallel Programming Aims and scope Submit manuscript

Abstract

Generic programming is an especially attractive paradigm for developing libraries for high-performance computing because it simultaneously emphasizes generality and efficiency. In the generic programming approach, interfaces are based on sets of specified requirements on types, rather than on any particular types, allowing algorithms to inter-operate with any data types meeting the necessary requirements. These sets of requirements, known as concepts, can specify syntactic as well as semantic requirements. Besides providing a powerful means of describing interfaces to maximize software reuse, concepts provide a uniform mechanism for more closely coupling libraries with compilers and for effecting domain-specific library-based compiler extensions. To realize this goal however, programming languages and their associated tools must support concepts as first-class constructs. In this paper we advocate better syntactic and semantic support to make concepts first-class and present results demonstrating the kinds of improvements that are possible with static checking, compiler optimization, and algorithm correctness proofs for generic libraries based on concepts.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

References

  1. M. H. Austern (1999) Generic Programming and the STL. Professional computing series Addison-Wesley Reading MA

    Google Scholar 

  2. R. Garcia, J. Järvi, A. Lumsdaine, J. Siek, and J. Willcock, A Comparative Study of Language Support for Generic Programming, Proceedings of the 18th ACM SIGPLAN Conference on Object-oriented Programming, Systems, Languages, and Applications, pp. 115–134, ACM press, New York (October 2003).

  3. SGI, Standard Template Library Programmer’s Guide, http://www.sgi.com/tech/stl/ (1997).

  4. R. D. Jenks R. S. Sutor (1992) AXIOM: The Scientific Computation System Springer New York

    Google Scholar 

  5. M. Clavel, F Durán, S. Eker, P Lincoln, N. Martí-Oliet, J. Meseguer, and J. F. Quesada, Maude: Specification and Programming in Rewriting Logic, Theoretical Computer Science, 285:187–243 (2001), URL: http://citeseer.nj.nec.com/clavel01maude.html.

  6. D. Gregor and S. Schupp, Making the Usage of STL Safe, J. Gibbons and J. Jeuring (eds.), Proceedings of the IFIP TC2 Working Conference on Generic Programming, pp. 127–140, Kluwer, Boston (2002).

  7. D. Gregor, High-Level Static Analysis for Generic Libraries, Ph.D. thesis, Rensselaer Polytechnic Institute (April 2004).

  8. D. R. Musser, Algorithm Concepts, http://www.cs.rpi.edu/∼musser/gp/algorithm- concepts (2003).

  9. J. Siek L.-Q. Lee A. Lumsdaine (2002) The Boost Graph Library: User Guide and Reference Manual Addison-Wesley Reading MA

    Google Scholar 

  10. D. Kapur and D. Musser, Tecton: A Framework for Specifying and Verifying Generic System Components, Technical Report RPI-92-20, Department of Computer Science, Rensselaer Polytechnic Institute, Troy, New York 12180 (July 1992), URL http:// citeseer.ist.psu.edu/kapur92tecton.html.

  11. Silicon Graphics, Inc., SGI Implementation of the Standard Template Library (2004), http://www.sgi.com/tech/stl/.

  12. A. A. Stepanov and M. Lee, The Standard Template Library, Technical Report X3J16/94-0095, WG21/N0482, ISO Programming Language C++ Project (May 1994).

  13. A. Kershenbaum, D. Musser, and A. Stepanov, Higher Order Imperative Programming, Technical Report 88-10, Rensselaer Polytechnic Institute (1988).

  14. International Standardization Organization (ISO), ANSI/ISO Standard 14882, Programming Language C++, 1 rue de Varembé, Case postale 56, CH-1211 Genève 20, Switzerland (1998).

  15. L. Zolman, An STL Error Message Decryptor for Visual C++, C/C++ Users Journal (July 2001).

  16. J. Siek and A. Lumsdaine, Concept Checking: Binding Parametric Polymorphism in C++, First Workshop an C++ Template Programming (October 2000).

  17. J. Willcock, J. Siek, and A. Lumsdaine, Caramel: A Concept Representation System for Generic Programming, Second Workshop on C++ Template Programming (October 2001).

  18. J. Järvi, J. Willcock, H. Hinnant, and A. Lumsdaine, Function Overloading Based on Arbitrary Properties of Types, C/C++ Users J. 21(6):25–32 (June 2003).

  19. B. Liskov, A. Snyder, R. Atkinson, and C. Schaffert, Abstraction mechanisms in CLU, Comm. ACM, 20(8):564–576 (1977).

    Google Scholar 

  20. M. Day, R. Gruber, B. Liskov, and A. C. Myers, Subtypes vs. Where Clauses: Constraining Parametric Polymorphism, OOPSLA, pp. 156–158 (1995).

  21. United States Department of Defense, The Programming Language Ada: Reference Manual, ANSI/MIL-STD-1815A-1983 edn. (February 1983).

  22. P. Wadler and S. Blott, How to Make ad-hoc Polymorphism Less ad-hoc, ACM Symposium on Principles of Programming Languages, pp. 60–76, ACM (January 1989).

  23. N. Myers, A New and Useful Technique: “Traits”, C++ Report, 7(5):32–35 (June 1995).

  24. J. Järvi, A. Lurnsdaine, J. Siek, and J. Willcock, An Analysis of Constrained Polymorphism for Generic Programming, K. Davis and J. Striegnitz (eds.), Multiparadigm Programming in Object-Oriented Languages Workshop (MPOOL) at OOPSLA, Anaheim, CA (October 2003).

  25. C. Chambers and the Cecil Group, The Cecil Language: Specification and Rationale, Version 3.1, University of Washington, Computer Science and Engineering (December 2002), http://www.cs.washington.edu/research/projects/cecil/.

  26. S. P. Jones, M. Jones, and E. Meijer, Type classes: an exploration of the design space, Haskell Workshop (June 1997).

  27. X. S. Li, J. W. Dermmel, D. H. Bailey, G. Henry, Y. Hida, J. Iskandar, W. Kahan, S. Y. Kang, A. Kapur, M. C. Martin, B. J. Thompson, T. Tung, and D. J. Yoo, Design, Implementation and Testing of Extended and Mixed Precision BLAS, ACM Trans. on Math. Software, 28(2):152–205 (June 2002).

  28. A. Koenig B. E. Moo (2000) Accelerated C++ Addison-Wesley Reading, MA

    Google Scholar 

  29. S. Schupp D. Gregor D. Musser S.-M. Liu (2002) ArticleTitleSemantic and behaviorial library transformations Special Issue of the J. Inform. Software Technol. 44 IssueID13 797–810

    Google Scholar 

  30. The LiDIA Group, LiDIA—A C++ Library for Computational Number Theory, http://www.informatik.tu-darmstadt.de/TI/LiDIA/.

  31. S. Schupp, D. Gregor, D. R. Musser, and S.-M. Liu, User-Extensible Simplification–Type-Based Optimizer Generators, International Conference on Compiler Construction, number 2027 in LNCS, pp. 86–101 (2001).

  32. J. Siek, Boost Concept Check Library, Boost (2000), http://www.boost.org/libs/concept_check/.

  33. B. Stroustrup and G. Dos Reis, Concepts—Design Choices for Template Argument Checking, Technical Report N1522=03-0105, ISO/IEC JTC 1, Information Technology, Subcommittee SC 22, Programming Language C++ (October 2003), http://anubis.dkuug.dk/jtc1/sc22/wg2l.

  34. B. Stroustrup, Concepts—A More Abstract Complement to Type Checking, Technical Report N1510=03-0093, ISO/IEC JTC 1, Information Technology, Subcommittee SC 22, Programming Language C++ (October 2003), http://anubis.dkuug.dk/jtcl/sc22/wg21.

  35. B. Stroustrup and G. Dos Reis, Concepts – syntax and composition, Technical Report N1536=03-0119, ISO/IEC JTC 1, Information Technology, Subcommittee SC 22, Programming Language C++ (October 2003), http://anubis.dkuug.dk/jtc1/sc22/wg2l.

  36. K. Arkoudas, Denotational Proof Languages, Ph.D. thesis, MIT, Cambridge, MA (2000).

  37. M. Kulkarni and D. R. Musser, Concept Taxonomy for Distributed Algorithms, http://www.cs.rpi.edu/∼kulkam/concepts/pagedir/concindex.html.

  38. J. G. Siek and A. Lumsdaine, The Matrix Template Library: A Generic Programming Approach to High Performance Numerical Linear Algebra, in Proc. of International Symposium on Computing in Object-Oriented Parallel Environments (1998).

Download references

Author information

Authors and Affiliations

  1. Open Systems Laboratory, Indiana University, Bloomington, IN, USA

    Douglas Gregor & Andrew Lumsdaine

  2. Department of Computer Science, Texas A&M University, College Station, TX, USA

    Jaakko Järvi

  3. Computer Science Department, Rensselaer Polytechnic Institute, Troy, NY, USA

    Mayuresh Kulkarni & David Musser

  4. Department of Computing Science, Chalmers University of Technology, S-41296, Göteborg, Sweden

    Sibylle Schupp

Authors
  1. Douglas Gregor
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Jaakko Järvi
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Mayuresh Kulkarni
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Andrew Lumsdaine
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. David Musser
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Sibylle Schupp
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Douglas Gregor.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Gregor, D., Järvi, J., Kulkarni, M. et al. Generic Programming and High-Performance Libraries. Int J Parallel Prog 33, 145–164 (2005). https://doi.org/10.1007/s10766-005-3580-8

Download citation

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10766-005-3580-8

Keywords

Search

Navigation