Skip to main content
SpringerLink
Log in

A simple framework to calculate the reaching definition of array references and its use in subscript array analysis

  • Conference paper
  • First Online:
Parallel and Distributed Processing (IPPS 1999)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 1586))

Included in the following conference series:

Abstract

The property analysis of subscript arrays can be used to facilitate the automatic detection of parallelism in sparse/irregular programs that use indirectly accessed arrays. In order for property analysis to work, array reaching definition information is needed. In this paper, we present a framework to efficiently calculate the array reaching definition. This method is designed to handle the common program patterns in real programs. We use some available techniques as the building components, such as data dependence tests and array summary set representations and operations. Our method is more efficient as well as more flexible than the existing techniques.

This work is supported in part by Army contract DABT63-95-C-0097; Army contract N66001-97-C-8532; NSF contract MIP-9619351; and a Partnership Award from IBM. This work is not necessarily representative of the positions or policies of the Army or Government.

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

Access this chapter

Log in via an institution

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. V. Balasundaram and K. Kennedy. A technique for summarizing data access and its use in parallelism-enhancing transformations. In Proceedings of the ACM SIGPLAN’89 Conference on Programming Language Design and Implementation (PLDI), Portland, OR, June 1989.

    Google Scholar 

  2. William Blume, Rudolf Eigenmann, Keith Faigin, John Grout, Jay Hoeflinger, David Padua, Paul Petersen, William Pottenger, Lawrence Rauchwerger, Peng Tu, and Stephen weatherford. Polaris: Improving the effectiveness of parallelizing compilers. In Keshav Pingali, Uptal Banerjee, David Gelernter, Alex Nicolau, and David Padua, editors, Proceedings of the 7th International Workshop on Languages and Compilers for Parallel Computing, Lecture Notes in Computer Science, pages 141–154, Ithaca, New York, August 8–10, 1994. Springer-Verlag.

    Google Scholar 

  3. Rudolf Eigenmann and William Blume. An effectiveness study of parallelizing compiler techniques. In Proceedings of the 1991 International Conference on Parallel Processing, volume II, Software, pages II–17–II–25, Boca Raton, FL, August 1991. CRC Press.

    Google Scholar 

  4. P. Feautrier. Dataflow analysis of scalar and array references. International Journal of Parallel Programming, 20(1):23–52, February 1991.

    Article  MATH  Google Scholar 

  5. Thomas Gross and Peter Steenkiste. Structured dataflow analysis for arrays and its use in an optimizing compiler. Software Practice and Experience. 20(2):133–155, February 1990.

    Google Scholar 

  6. Junjie Gu, Zhiyuan Li, and Gyungho Lee. Symbolic array dataflow analysis for array privatization and program parallelization. In Sidney Karin, editor, Proceedings of the 1995 ACM/IEEE Supercomputing Conference, December 3–8, 1995, San Diego Convention Center, San Diego, CA, USA, New York, NY 10036, USA, 1995. ACM Press and IEEE Computer Society Press.

    Google Scholar 

  7. P. Havlak. Interprocedural Symbolic analysis. PhD thesis, Rice University, May 1994.

    Google Scholar 

  8. Y. Lin and D. Padua. On the automatic parallelization of sparse and irregular fortran programs. In Proc. of 4th Workshop on Languages, Compilers, and Runtime Systems for Scalable Computers (LCR98), volume 1511 of Lecture Notes in Computer Science, pages 41–56. Springer-Verlag, Pittsburgh, PA, 1998.

    Google Scholar 

  9. Vadim Maslov. Delinearization: An efficient way to break multiloop dependence equations. In Proceedings of the Conference on Programming Language Design and Implementation (PLDI), volume 27, pages 152–161, New York, NY, July 1992. ACM Press.

    Google Scholar 

  10. Vadim Maslov. Lazy array data-flow dependence analysis. In ACM, editor, Proceedings of 21st Annual ACM SIGACT-SIGPLAN Symposium on Principles of Programming Languages, pages 311–325, New York, NY, USA, ???? 1994. ACM Press.

    Chapter  Google Scholar 

  11. Yunheung Paek, Jay Hoeflinger, and David Padua. Simplification of array access patterns for compiler optimizations. In Proceedings of the ACM SIGPLAN’98 Conference on Programming Language Design and Implementation (PLDI), pages 60–71, Montreal, Canada, 17–19 June 1998.

    Google Scholar 

  12. William Pugh and David Wonnacott. An exact method for analysis of value-based array data dependences. In Proceedings of the Sixth Annual Workshop on rogramming Languages and Compilers for Parallel Computing, December 93.

    Google Scholar 

  13. R. Triolet, F. Irigoin, and P. Feautrier. Direct parallelization of call statements. In Proceedings of the SIGPLAN’86 Symposium on Compiler Construction, pages 176–185, Palo Alto, CA, July 1986.

    Google Scholar 

  14. Peng Tu and David Padua. Automatic array privatization. In Uptal Banerjee, David Gelernter, Alex Nicolau, and David Padua, editors, Proceedings of the 6th International Workshop on Languages and Compilers for Parallel Computing, Lecture Notes in Computer Science, pages 500–521, Portland, Oregon, August 12–14, 1993. Intel Corp. and the Portland Group, Inc., Springer-Verlag.

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Computer Science, University of Illinois at Urbana-Champaign, Urbana-Champaign, USA

    Yuan Lin & David Padua

Authors
  1. Yuan Lin
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. David Padua
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

José Rolim Frank Mueller Albert Y. Zomaya Fikret Ercal Stephan Olariu Binoy Ravindran Jan Gustafsson Hiroaki Takada Ron Olsson Laxmikant V. Kale Pete Beckman Matthew Haines Hossam ElGindy Denis Caromel Serge Chaumette Geoffrey Fox Yi Pan Keqin Li Tao Yang G. Chiola G. Conte L. V. Mancini Domenique Méry Beverly Sanders Devesh Bhatt Viktor Prasanna

Rights and permissions

Reprints and permissions

Copyright information

© 1999 Springer-Verlag

About this paper

Cite this paper

Lin, Y., Padua, D. (1999). A simple framework to calculate the reaching definition of array references and its use in subscript array analysis. In: Rolim, J., et al. Parallel and Distributed Processing. IPPS 1999. Lecture Notes in Computer Science, vol 1586. Springer, Berlin, Heidelberg . https://doi.org/10.1007/BFb0097989

Download citation

  • DOI: https://doi.org/10.1007/BFb0097989

  • Published:

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-65831-3

  • Online ISBN: 978-3-540-48932-0

  • eBook Packages: Springer Book Archive

Publish with us

Policies and ethics

Search

Navigation