Advertisement

Expansion-Based Removal of Semantic Partial Redundancies

  • Jens Knoop
  • Oliver Rüthing
  • Bernhard Steffen
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 1575)

Abstract

We develop an expansion-based algorithm for semantic partial redundancy elimination (SPRE), which overcomes the central drawbacks of the state-of-the-art approaches, which leave the program structure invariant: they fail to eliminate all partial redundancies even for acyclic programs. Besides being optimal for acyclic programs, our algorithm is unique in eliminating all partial k-redundancies, a new class of redundancies which is characterised by the number k of loop iterations across which values have to be kept. These optimality results come at the price of an in the worst case exponential program growth. The new technique is thus tailored for optimizing the typically considerably small computational “hot” spots of a program. Here it is particularly promising because its structural simplicity supports extensions to uniformly capture further powerful optimisations like constant propagation or strength reduction in a mutually supportive way.

Keywords

Strength Reduction Outgoing Edge Original Program Loop Iteration Program Point 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

References

  1. 1.
    Aho, A.V., Sethi, R., Ullman, J.D.: Compilers: Principles, Techniques and Tools. Addison-Wesley, Reading (1985)Google Scholar
  2. 2.
    Allen, F.E., Cocke, J., Kennedy, K.: Reduction of operator strength. In: Muchnick, S.S., Jones, N.D. (eds.) Program Flow Analysis: Theory and Applications, ch. 3, pp. 79–101. Prentice Hall, Englewood Cliffs (1981)Google Scholar
  3. 3.
    Bodík, R., Anik, S.: Path-sensitive value-flow analysis. In: Conf. Rec. 25th Symp. on Principles of Programming Languages POPL 1998, pp. 237–251. ACM, New York (1998)Google Scholar
  4. 4.
    Bodík, R., Gupta, R., Soffa, M.-L.: Complete removal of redundant expressions. In: Proc. ACM SIGPLAN Conf. Prog. Lang. Design and Impl. PLDI 1998. ACM SIGPLAN Not., vol. 33, pp. 1–14 (1998)Google Scholar
  5. 5.
    Click, C.: Global code motion/global value numbering. In: Proc. ACM SIGPLAN Conf. Prog. Lang. Design and Impl. PLDI 1995. ACM SIGPLAN Not., vol. 30(6), pp. 246–257 (1995)Google Scholar
  6. 6.
    Cocke, J., Kennedy, K.: An algorithm for reduction of operator strength. Comm. ACM 20(11), 850–856 (1977)zbMATHCrossRefGoogle Scholar
  7. 7.
    Cocke, J., Schwartz, J.T.: Programming languages and their compilers. In: Courant Inst. Math. Sciences, NY (1970)Google Scholar
  8. 8.
    Cytron, R., Ferrante, J., Rosen, B.K., Wegman, M.N., Zadeck, F.K.: Efficiently computing static single assignment form and the control dependence graph. ACM Trans. Prog. Lang. Syst. 13(4), 451–490 (1991)CrossRefGoogle Scholar
  9. 9.
    Kam, J.B., Ullman, J.D.: Monotone data flow analysis frameworks. Acta Informatica 7, 305–317 (1977)zbMATHCrossRefMathSciNetGoogle Scholar
  10. 10.
    Kildall, G.A.: A unified approach to global program optimization. In: Conf. Rec. 1st Symp. Principles of Prog. Lang. POPL 1973, pp. 194–206. ACM, New York (1973)Google Scholar
  11. 11.
    Knoop, J., Rüthing, O., Steffen, B.: The power of assignment motion. In: Proc. ACM SIGPLAN Conf. on Prog. Lang. Design and Impl. PLDI 1995. ACM SIGPLAN Not., vol. 30(6), pp. 233–245 (1995)Google Scholar
  12. 12.
    Knoop, J., Rüthing, O., Steffen, B.: Code motion and code placement: Just synomyms? In: Hankin, C. (ed.) ESOP 1998. LNCS, vol. 1381, pp. 154–169. Springer, Heidelberg (1998)CrossRefGoogle Scholar
  13. 13.
    Morel, E., Renvoise, C.: Global optimization by suppression of partial redundancies. Comm. ACM 22(2), 96–103 (1979)zbMATHCrossRefMathSciNetGoogle Scholar
  14. 14.
    Reif, J.H., Lewis, R.: Symbolic evaluation and the global value graph. In: Conf. Rec. 4th Symp. Principles of Prog. Lang. POPL 1977, pp. 104–118. ACM, New York (1977)Google Scholar
  15. 15.
    Rosen, B.K., Wegman, M.N., Zadeck, F.K.: Global value numbers and redundant computations. In: Conf. Rec. 15th Symp. Principles of Prog. Lang. POPL 1988, pp. 2–27. ACM, New York (1988)Google Scholar
  16. 16.
    Steffen, B.: Optimal run time optimization - Proved by a new look at abstract interpretations. In: Ehrig, H., Levi, G., Montanari, U. (eds.) CAAP 1987 and TAPSOFT 1987. LNCS, vol. 249, pp. 52–68. Springer, Heidelberg (1987)Google Scholar
  17. 17.
    Steffen, B.: Property-oriented expansion. In: Cousot, R., Schmidt, D.A. (eds.) SAS 1996. LNCS, vol. 1145. Springer, Heidelberg (1996)Google Scholar
  18. 18.
    Steffen, B., Knoop, J., Rüthing, O.: The value flow graph: A program representation for optimal program transformations. In: Jones, N.D. (ed.) ESOP 1990. LNCS, vol. 432. Springer, Heidelberg (1990)Google Scholar
  19. 19.
    Steffen, B., Knoop, J., Rüthing, O.: Efficient code motion and an adaption to strength reduction. In: Abramsky, S. (ed.) TAPSOFT 1991, CCPSD 1991, and ADC-Talks 1991. LNCS, vol. 494. Springer, Heidelberg (1991)Google Scholar
  20. 20.
    Whitfield, D., Soffa, M.L.: An approach to ordering optimizing transformations. In: Proc. 2nd ACM SIGPLAN Symp. on Principles and Practice of Parallel Programming PPOPP 1990. ACM SIGPLAN Not., vol. 25(3), pp. 137–147 (1990)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 1999

Authors and Affiliations

  • Jens Knoop
    • 1
  • Oliver Rüthing
    • 1
  • Bernhard Steffen
    • 1
  1. 1.Universität Dortmund Baroper Str. 301DortmundGermany

Personalised recommendations