Article

Toward efficient flow-sensitive induction variable analysis and dependence testing for loop optimization

Authors:

Robert A. van Engelen,

Kyle A. GallivanAuthors Info & Claims

ACMSE '06: Proceedings of the 44th annual ACM Southeast Conference

Pages 1 - 6

https://doi.org/10.1145/1185448.1185450

Published: 10 March 2006 Publication History

Abstract

This paper presents a new approach to improve flow-sensitive induction variable analysis and data dependence testing on intermediate program representations, such as control-flow graphs with low-level operations representations in single static assignment forms. Current compiler techniques have difficulties optimizing loops that exhibit irregular control flow patterns. The inaccuracy of loop analysis results in conservative estimations of array-based data dependences in loops, which negatively affects the speedup of the loop via parallelization and vectorization. Our approach is based on a novel CR# (CR-sharp) algebra that effectively represents the value progressions of (conditionally) updated variables in loops. The CR# forms of induction variables are constructed with a new flow-sensitive induction variable recognition algorithm. We also developed a new CR#-based nonlinear data dependence test that enables loops to be more effectively optimized.

References

[1]

A. Aho, R. Sethi, and J. Ullman. Compilers: Principles, Techniques and Tools. Addison-Wesley Publishing Company, Reading MA, 1985.]]

Digital Library

[2]

O. Bachmann. Chains of Recurrences. PhD thesis, Kent State University, College of Arts and Sciences, 1996.]]

[3]

U. Banerjee. Dependence Analysis for Super computing. Kluwer, Boston, 1988.]]

Digital Library

[4]

D. Berlin, D. Edelsohn, and S. Pop. High-level loop optimizations for gcc. In Proceedings of the 2004 GCC Developers Summit, pages 37--54, 2004.]]

[5]

M. Gerlek, E. Stolz, and M. Wolfe. Beyond induction variables: Detecting and classifying sequences using a demand-driven SSA form. ACM Transactions on Programming Languages and Systems (TOPLAS), 17(1):85--122, jan 1995.]]

Digital Library

[6]

G. Goff, K. Kennedy, and C.-W. Tseng. Practical dependence testing. In proceedings of the ACM SIGPLAN '91 Conference on Programming Language Design and Implementation (PLDI), volume 26, pages 15--29, Toronto, Ontario, Canada, June 1991.]]

Digital Library

[7]

M. R. Haghighat and C. D. Polychronopoulos. Symbolic analysis for parallelizing compilers. ACM Transactions on Programming Languages and Systems, 18(4):477--518, July 1996.]]

Digital Library

[8]

S. Muchnick. Advanced Compiler Design and Implementation. Morgan Kaufmann, San Fransisco, CA, 1997.]]

Digital Library

[9]

D. Novillo. Tree SSA: A new optimization infrastructure for gcc. In Proceedings of the 2003 GCC Developers Summit, pages 181--193, 2003.]]

[10]

K. Psarris. Program analysis techniques for transforming programs for parallel systems. Parallel Computing, 28(3):455--469, 2003.]]

Digital Library

[11]

Z. Shen, Z. Li, and P.-C. Yew. An empirical study on array subscripts and data dependencies. In proceedings of the International Conference on Parallel Processing, volume 2, pages 145--152, 1989.]]

[12]

R. Tarjan. Depth first search and linear graph algorithms. SIAM Journal of Computing, 1(2):146--160, 1972.]]

Digital Library

[13]

P. Tu and D. Padua. Gated SSA-based demand-driven symbolic analysis for parallelizing compilers. In proceedings of the 9thACM International Conference on Supercomputing (ICS), pages 414--423, New York, jul 1995. ACM Press.]]

Digital Library

[14]

R. van Engelen. Efficient symbolic analysis for optimizing compilers. In proceedings of the ETAPS Conference on Compiler Construction 2001, LNCS 2027, pages 118--132, 2001.]]

Digital Library

[15]

R. van Engelen. The CR# algebra and its application in loop analysis and optimization. Technical report, Computer Science Dept., Florida State University, 2004.]]

[16]

R. van Engelen, J. Birch, and K. Gallivan. Array data dependence testing with the chains of recurrences algebra. In proceedings of the IEEE International Workshop on Innovative Architectures for Future Generation High-Performance Processors and Systems (IWIA), pages 70--81, January 2004.]]

Digital Library

[17]

R. van Engelen, J. Birch, Y. Shou, B. Walsh, and K. Gallivan. A unified framework for nonlinear dependence testing and symbolic analysis. In proceedings of the ACM International Conference on Supercomputing (ICS), pages 106--115, 2004.]]

Digital Library

[18]

M. Wolfe. Beyond induction variables. In ACM SIGPLAN'92 Conf. on Programming Language Design and Implementation, pages 162--174, San Fransisco, CA, 1992.]]

Digital Library

[19]

M. Wolfe. High Performance Compilers for Parallel Computers. Addison-Wesley, Redwood City, CA, 1996.]]

Digital Library

[20]

P. Wu, A. Cohen, J. Hoeflinger, and D. Padua. Monotonic evolution: An alternative to induction variable substitution for dependence analysis. In proceedings of the ACM International Conference on Supercomputing (ICS), pages 78--91, 2001.]]

Digital Library

[21]

E. Zima. Recurrent relations and speed-up of computations using computer algebra systems. In proceedings of DISCO'92, pages 152--161. LNCS 721, 1992.]]

Digital Library

[22]

H. Zima and B. Chapman. Supercompilers for Parallel and Vector Computers. ACM Press, New York, 1990.]]

Cited By

Gampe Avon Ronne JNiedzielski DVasek JPsarris K(2011)Safe, multiphase bounds check elimination in JavaSoftware—Practice & Experience10.1002/spe.102841:7(753-788)Online publication date: 1-Jun-2011
https://dl.acm.org/doi/10.1002/spe.1028
Birch JPsarris K(2008)Discovering Maximum Parallelization Using Advanced Data Dependence AnalysisProceedings of the 2008 10th IEEE International Conference on High Performance Computing and Communications10.1109/HPCC.2008.145(103-112)Online publication date: 25-Sep-2008
https://dl.acm.org/doi/10.1109/HPCC.2008.145
Shou YEngelen RBirch J(2007)Flow-Sensitive Loop-Variant Variable Classification in Linear TimeLanguages and Compilers for Parallel Computing10.1007/978-3-540-85261-2_22(323-337)Online publication date: 1-Oct-2007
https://dl.acm.org/doi/10.1007/978-3-540-85261-2_22
Show More Cited By

Index Terms

Toward efficient flow-sensitive induction variable analysis and dependence testing for loop optimization
1. Software and its engineering
  1. Software notations and tools
    1. Compilers

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cover image ACM Other conferences

ACMSE '06: Proceedings of the 44th annual ACM Southeast Conference

March 2006

823 pages

ISBN:1595933158

DOI:10.1145/1185448

General Chair:
Ronaldo Menezes
Florida Institute of Technology

Copyright © 2006 ACM.

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Published: 10 March 2006

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ACM SE06

ACM SE06: ACM Southeast Regional Conference

March 10 - 12, 2006

Florida, Melbourne

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ACMSE '06 Paper Acceptance Rate 100 of 244 submissions, 41%;

Overall Acceptance Rate 502 of 1,023 submissions, 49%

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Cited By

Gampe Avon Ronne JNiedzielski DVasek JPsarris K(2011)Safe, multiphase bounds check elimination in JavaSoftware—Practice & Experience10.1002/spe.102841:7(753-788)Online publication date: 1-Jun-2011
https://dl.acm.org/doi/10.1002/spe.1028
Birch JPsarris K(2008)Discovering Maximum Parallelization Using Advanced Data Dependence AnalysisProceedings of the 2008 10th IEEE International Conference on High Performance Computing and Communications10.1109/HPCC.2008.145(103-112)Online publication date: 25-Sep-2008
https://dl.acm.org/doi/10.1109/HPCC.2008.145
Shou YEngelen RBirch J(2007)Flow-Sensitive Loop-Variant Variable Classification in Linear TimeLanguages and Compilers for Parallel Computing10.1007/978-3-540-85261-2_22(323-337)Online publication date: 1-Oct-2007
https://dl.acm.org/doi/10.1007/978-3-540-85261-2_22
Birch Jvan Engelen RGallivan KShou YAltman ESkadron KZorn B(2006)An empirical evaluation of chains of recurrences for array dependence testingProceedings of the 15th international conference on Parallel architectures and compilation techniques10.1145/1152154.1152198(295-304)Online publication date: 16-Sep-2006
https://dl.acm.org/doi/10.1145/1152154.1152198

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