Efficient symbolic analysis for optimizing compilers

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 2027, Issue , 2001, Pages 118-132

  Van Engelen, Robert A ^a  

^a Florida State University   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ARTIFICIAL INTELLIGENCE; COMPUTER SCIENCE; COMPUTERS;

INDUCTION VARIABLE SUBSTITUTION; INDUCTION VARIABLES; LOOP OPTIMIZATIONS; LOOP PARALLELIZATION; LOOP TRANSFORMATION; OPTIMIZING COMPILERS; PARALLELIZATION TECHNIQUES; STRENGTH REDUCTION;

PROGRAM COMPILERS;

EID: 84928660150     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/3-540-45306-7_9     Document Type: Conference Paper

References (21)

1. A. Aho, R. Sethi, and J. Ullman. Compilers: Principles, Techniques and Tools. Addison-Wesley Publishing Company, Reading MA, 1985.
2. F. Allen, J. Cocke, and K. Kennedy. Reduction of operator strength. In S. Munchnick and N. Jones, editors, Program Flow Analysis, pages 79-101, New-Jersey, 1981. Prentice-Hall.
3. Z. Ammerguallat and W.L. Harrison III. Automatic recognition of induction variables and recurrence relations by abstract interpretation. In ACM SIGPLAN'90 Conference on Programming Language Design and Implementation, pages 283-295, White Plains, NY, 1990. Arts and Sciences, 1996.
4. O. Bachmann, P.S. Wang, and E.V. Zima. Chains of recurrences - a method to expedite the evaluation of closed-form functions. In International Symposium on Symbolic and Algebraic Computing, pages 242-249, Oxford, 1994. ACM.
5. W. Blume and R. Eigenmann. Demand-driven, symbolic range propagation. In 8th International workshop on Languages and Compilers for Parallel Computing, pages 141-160, Columbus, Ohio, USA, August 1995.
6. R. Eigenmann, J. Hoeflinger, G. Jaxon, Z. Li, and D.A. Padua. Restructuring fortran programs for cedar. In ICPP, volume 1, pages 57-66, St. Charles, Illinois, 1991.
7. R. Eigenmann, J. Hoeflinger, Z. Li, and D.A. Padua. Experience in the automatic parallelization of four perfect-benchmark programs. In 4th Annual Workshop on Languages and Compilers for Parallel Computing, LNCS 589, pages 65-83, Santa Clara, CA, 1991. Springer Verlag.
8. T. Fahringer. Efficient symbolic analysis for parallelizing compilers and performance estimators. Supercomputing, 12(3):227-252, May 1998.
9. Mohammad R. Haghighat. Symbolic Analysis for Parallelizing Compilers. Kluwer Academic Publishers, 1995.
10. M.R. Haghighat and C.D. Polychronopoulos. Symbolic program analysis and optimization for parallelizing compilers. In 5th Annual Workshop on Languages and Compilers for Parallel Computing, LNCS 757, pages 538-562, New Haven, Connecticut, 1992. Springer Verlag.
11. P. Knupp and S. Steinberg. Fundamentals of Grid Generation. CRC Press, 1994.
12. S. Munchnick. Advanced Compiler Design and Implementation. Morgan Kaufmann, San Fransisco, CA, 1997.
13. J.P. Singh and J.L. Hennessy. An emperical investigation of the efiectiviness and limitations of automatic parallelization. In N. Suzuki, editor, Shared Memory Multiprocessing, pages 203- 207. MIT press, Cambridge MA, 1992.
14. R. van Engelen, D. Whalley, and X. Yuan. Automatic validation of code-improving transformations. In ACM SIGPLAN Workshop on Language, Compilers, and Tools for Embedded Systems, 2000.
15. R.A. van Engelen. Symbolic evaluation of chains of recurrences for loop optimization. Technical report, TR-000102, Computer Science Deptartment, Florida State University, 2000. Available from http://www.cs.fsu.edu/~engelen/cr.ps.gz.
16. R.A. van Engelen, L. Wolters, and G. Cats. Ctadel: A generator of multi-platform high performance codes for pde-based scientific applications. In 10th ACM International Conference on Supercomputing, pages 86-93, New York, 1996. ACM Press.
17. R.A. van Engelen, L. Wolters, and G. Cats. Tomorrow's weather forecast: Automatic code generation for atmospheric modeling. IEEE Computational Science and Engineering, 4(3):22-31, July/September 1997.
18. M.J. Wolfe. Beyond induction variables. In ACM SIGPLAN'92 Conference on Programming Language Design and Implementation, pages 162-174, San Fransisco, CA, 1992.
19. M.J. Wolfe. High Performance Compilers for Parallel Computers. Addison-Wesley, Redwood City, CA, 1996.
20. E.V. Zima. Recurrent relations and speed-up of computations using computer algebra systems. In DISCO'92, pages 152- 161. LNCS 721, 1992.
21. H. Zima. Supercompilers for Parallel and Vector Computers. ACM Press, New York, 1990.