Interprocedural induction variable analysis

International Journal of Foundations of Computer Science

Volumn 14, Issue 3, 2003, Pages 405-423

  Tang, Peiyi ^a   Yew, PenChung ^b  

^a University of Arkansas at Little Rock ^*  (United States)

^b University of Minnesota   (United States)

Author keywords

call graphs; extended full program representation (EFPR) graphs; induction variable analysis; Interprocedural induction variables; interprodural factored usedef (IFUD) graphs; recursive procedure call

Indexed keywords

EID: 34248360078     PISSN: 01290541     EISSN: None     Source Type: Journal    
DOI: 10.1142/S0129054103001819     Document Type: Conference Paper

References (14)

1. Z. Li and P.-C. Yew, "Interprocedural analysis for parallel computing," Proc. 1988International Conference on Parallel Processing, Vol. II, Aug. 1988, pp. 225-244
2. P. Tang, "Exact side effects for interprocedural dependence analysis," Proc. 1993ACM International Conference on Supercomputing, Tokyo, Japan, Jul. 1993, pp.137-146
3. Y. Paek, J. Hoeflinger, and D. Padua, "Simplification of array access patterns forcompiler optimizations," Proc. 1998 ACM SIGPLAN Conference on ProgrammingLanguage Design and Implementation, Jun. 1998, pp. 60-71
4. J. Hoeflinger and Y. Paek, "The access region test," Proc 1999 International Workshopon Languages and Compilers for Parallel Computing, La Jolla, CA, Aug. 1999,pp. 271-285
5. M. Wolfe, "Beyond induction variables," Proc. 1992 ACM SIGPLAN Conferenceon Programming Language Design and Implementation, Jun. 1992, pp. 162-174
6. M. Wolfe, High Performance Compilers for Parallel Computing (Addison-Wesley,1995)
7. F. E. Allen, J. Cocke, and K. Kennedy, "Reduction of operator strength," in ProgramFlow Analysis: Theory and Applications, eds. S. S. Muchnick and N. D. Jones(Prentice-Hall, 1981) pp. 79-101
8. J. Cocke and K. Kennedy, "An algorithm for reduction of operator strength," Communicationsof the A CM 20(11) (1977) 850-856
9. Z. Ammarguellat and W. L. Harrison III, "Automatic recognition of inductionvariables and recurrence relations by abstract interpretation," Proc. ACMSIGPLAN Conference on Programming Language Design and Implementation, Jun.1990, pp. 283-295
10. M. R. Haghighat and C. D. Polychronopoulos, "Symbolic analysis: A basis forparallelization, optimization, and scheduling of programs," Proc. 1993 InternationalWorkshop on Languages and Compilers for Parallel Computing, Aug. 1993, pp.567-585
11. M. R. Haghighat, Symbolic Analysis for Parallelizing Compilers (Kluwer AcademicPublishers, 1995)
12. G. Agrawal, J. Salts, and R. Das, "Interprocedural partial redundancy eliminationand its applications to distributed memory compilation," Proc. ACMSIGPLAN Conference on Programming Language Design and Implementation, Jun.1995, pp. 258-269
13. A. V. Aho, R. Sethi, and J. D. Ullman, Compilers: Principles, Techniques andTools (Addison-Wesley Publishing Company, 1986)
14. R. Cytron, J. Ferrante, B. K. Rosen, M. N. Wegman, and F. K. Zadeck, "Efficientlycomputing static single assignment form and the control dependence graph," ACMTransactions on Programming Languages and Systems 13(4) (1991) 451-490.