Skip to main content
Log in

Fast Evaluation of Partial Derivatives and Interval Slopes

  • Published:
Reliable Computing

Abstract

For functions that share intermediate results, the computation of partial derivatives can be modeled by node condensation on graphs. In this case, mixed evaluation strategies can outperform either the backward or the forward mode of automatic differentiation. In this paper we present new algorithms and heuristics to find good evaluation strategies for partial derivatives. We show that these techniques not only apply for interval derivatives but also for interval slopes.

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

Access this article

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

Instant access to the full article PDF.

Similar content being viewed by others

References

  1. Baur, W. and Strassen, V.: The Complexity of Partial Derivatives, Theoretical Computer Science 22 (1983), pp. 317–330.

    Google Scholar 

  2. Bischof, C. and Haghighat, M.: Hierarchical Approaches to Automatic Differentiation, in: Berz, M., Bischof, C., Corliss, G., and Griewank, A. (eds), Computational Differentiation: Techniques, Applications, and Tools, SIAM, Philadelphia, Pennsylvania, 1996, pp. 83–94.

    Google Scholar 

  3. Bliek, C.: Computer Methods for Design Automation, PhD thesis, Massachusetts Institute of Technology, Cambridge, Massachusetts, 1992.

    Google Scholar 

  4. Duff, I. S., Erisman, A. M., and Reid, J. K.: Direct Methods for Sparse Matrices, Clarendon Press, Oxford, 1986.

    Google Scholar 

  5. Griewank, A.: On Automatic Differentiation, in: Iri, M. and Tanabe, K. (eds), Mathematical Programming, KTK Scientific Publishers, Tokyo, 1989, pp. 83–107.

    Google Scholar 

  6. Griewank, A.: Automatic Evaluation of First and Higher-Derivative Vectors, International Series of Numerical Mathematics 97, Birkhäuser Verlag, 1991, pp. 135–148.

    Google Scholar 

  7. Hansen, E. R.: Global Optimization Using Interval Analysis, Marcel Dekker, New York, 1992.

    Google Scholar 

  8. Iri, M.: Simultaneous Computation of Functions, Partial Derivatives and Estimates of Rounding Errors—Complexity and Practicality, Japan Journal of Applied Mathematics 1 (1984), pp. 223–252.

    Google Scholar 

  9. Neumaier, A.: Interval Methods for Systems of Equations, Cambridge University Press, 1990.

  10. Parter, S.: The Use of Linear Graphs in Gauss Elimination, SIAM Review 3 (2) (1961), pp. 119–130.

    Google Scholar 

  11. Rose, D. J. and Tarjan, R. E.: Algorithmic Aspects of Vertex Elimination on Directed Graphs, SIAM Journal of Applied Mathematics 34 (1) (1978), pp. 176–197.

    Google Scholar 

  12. Speelpenning, B.: Compiling Fast Partial Derivatives of Functions Given by Algorithms, PhD thesis, University of Illinois, Urbana-Champaign, Illinois, 1980.

    Google Scholar 

  13. Yoshida, T.: Derivation of a Computational Process for Partial Derivatives of Functions Using Transformations of a Graph, Transactions of IPSJ 11 (1987), pp. 1112–1120.

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Rights and permissions

Reprints and permissions

About this article

Cite this article

Bliek, C. Fast Evaluation of Partial Derivatives and Interval Slopes. Reliable Computing 3, 259–268 (1997). https://doi.org/10.1023/A:1009970723383

Download citation

  • Issue Date:

  • DOI: https://doi.org/10.1023/A:1009970723383

Keywords

Navigation