Fractal symbolic analysis

ACM Transactions on Programming Languages and Systems

Volumn 25, Issue 6, 2003, Pages 776-813

  Menon, Vijay ^a   Pingali, Keshav ^b,d   Mateev, Nikolay ^c,e  

^a INTEL CORPORATION   (United States)

^b Cornell University ^*  (United States)

^c HEWLETT PACKARD COMPANY   (United States)

^d School of Operations Research and Information Engineering   (United States)

^e HEWLETT PACKARD LABORATORIES   (United States)

Author keywords

Algorithms; Languages; Theory

Indexed keywords

FRACTAL SYMBOLIC ANALYSIS; LANGUAGES; MEMORY LOCATIONS; PROGRAM STATEMENTS;

ALGORITHMS; BUFFER STORAGE; CODES (SYMBOLS); COMPUTER PROGRAMMING LANGUAGES; MATHEMATICAL TRANSFORMATIONS; PROBLEM SOLVING; PROGRAM COMPILERS; RAPID PROTOTYPING; SEMANTICS; STORAGE ALLOCATION (COMPUTER);

FRACTALS;

EID: 4544346973     PISSN: 01640925     EISSN: None     Source Type: Journal    
DOI: 10.1145/945885.945888     Document Type: Article

References (32)

1. AHO, A. V., SETHI, R., AND ULLMAN, J. D. 1986. Compilers: Principles, Techniques and Tools, 2nd ed. Addison Wesley, Reading, MA.
2. ANDERSON, E., BAI, Z., BISCHOF, C., DEMMEL, J., DONGARRA, J., Du CROZ, J., GREENBAUM, A., HAMMARLING, S., MCKENNEY, A., OSTROUCHOV, S., AND SORENSEN, D., Eds. 1995. LAPACK Users' Guide. 2nd ed. SIAM, Philadelphia, PA.
3. BANERJEE, U. 1989. A theory of loop permutations. In Proceedings of the Conference on Languages and Compilers for Parallel Computing. 54-74.
4. BARTH, A. AND KOZEN, D. 2002. Equational verification of cache blocking in lu decomposition using Kleene algebra with tests. Tech. rep. 2002-1865. Cornell University, Ithaca, NY.
5. BERNSTEIN, A. 1966. Analysis of programs for parallel processing. IEEE Trans. Electron. Comput. EC-15, 5, 757-763.
6. BRYANT, R. E. 1986. Graph-based algorithms for Boolean function manipulation. IEEE Trans. Comput. C35, 8 (Aug.), 677-691.
7. CARR, S. AND LEHOUCQ, R. B. 1997. Compiler blockability of dense matrix factorizations. ACM Trans. Math. Softw. 23, 3 (Sept.), 336-361.
8. CHAR, B., GEDDES, K., AND GONNET, G. 1983. The Maple symbolic computation system. SIGSAM Bulletin (ACM Special Interest Group on Symbolic and Algebraic Manipulation) 17, 3/4 (Aug./Nov.), 31-42.
9. n programming environment. ACM Trans. Program. Lang. Syst. 8, 4 (Oct.), 491-523.
10. CORMEN, T., LEISERSON, C., AND RIVEST, R. 1992. Introduction to Algorithms. MIT Press, Cambridge, MA.
11. DEROSE, L. A. 1996. Compiler techniques for MATLAB programs. Tech. rep. 1956. Department of Computer Science, University of Illinois at Urbana-Champaign, Urbana, IL.
12. FEAUTRIER, P. 1991. Dataflow analysis of array and scalar references. Int. J. Parallel Program. 20, 1 (Feb.), 23-53.
13. FEAUTRIER, P. 1992. Some efficient solutions to the affine scheduling problem - part 1: One dimensional time. Int. J. Parallel Program. 21, 5 (Oct.), 313-348.
14. GOLUB, G. AND LOAN, C. V. 1996. Matrix Computations. The Johns Hopkins University Press, Baltimore, MD.
15. GUNTER, C. A. 1992. Semantics of Programming Languages. Foundations of Computing Series. MIT Press, Cambridge, MA.
16. HAGHIGHAT, M. R. AND POLYCHRONOPOULOS, C. D. 1996. Symbolic analysis for parallelizing compilers. ACM Trans. Program. Lang. Syst. 18, 4 (July), 477-518.
17. JOHNSON, S. M. 1963. Generation of permutations by adjacent transposition (in Technical Notes and Short Papers). Math. Comput. 17, 83 (July), 282-285.
18. KLOP, J. W. 1980. Combinatory Reduction Systems. Mathematisch Centrum, Amsterdam, The Netherlands.
19. KODUKULA, I., AHMED, N., AND PINGALI, K. 1997. Data-centric multi-level blocking. In Proceedings of the SIGPLAN'97 Conference on Programming Language Design and Implementation. 346-357.
20. LEROY, X. 1996. The Caml Light system, release 0.71. Documentation and user's manual. Tech. rep. INRIA, Sophia Antipolis, France. Available online from Projet Cristal at http://pauillac.inria.fr.
21. Li, W. AND PINGALI, K. 1994. A singular loop transformation based on non-singular matrices. Int. J. Parallel Program. 22, 2 (April), 183-205.
22. MASLOV, V. 1995. Enhancing array dataflow dependence analysis with on-demand global value propagation. In Proceedings of the International Conference on Supercomputing. 265-269.
23. MATEEV, N., MENON, V., AND PINGALI, K. 2000. Left-looking to right-looking and vice versa: An application of fractal symbolic analysis to linear algebra code restructuring. In Proceedings of Euro-Par (Munich, Germany).
24. METZGER, R. AND WEN, Z. 2000. Automatic Algorithm Recognition: A New Approach to Program Optimization. MIT Press, Cambridge, MA.
25. PUGH, W. 1992. The Omega test: A fast and practical integer programming algorithm for dependence analysis. Commun. ACM 35, 8(Aug.), 102-114.
26. RAUCHWERGER, L. AND PADUA, D. A. 1999. The LRPD test: Speculative run-time parallelization of loops with privatization and reduction parallelization. IEEE Trans. Parallel Distrib. Syst. 10, 2 (Feb.), 218-232.
27. REIF, J. H. AND TARJAN, R. E. 1982. Symbolic program analysis in almost linear time. SIAM J. Comput. 11, 1 (Feb.), 81-93.
28. RINARD, M. C. AND DINIZ, P. C. 1997. Commutativity analysis: A new analysis technique for parallelizing compilers. ACM Trans. Program. Lang. Syst. 19, 6 (Nov.), 942-991.
29. WEISER, M. 1984. Program slicing. IEEE Trans. Softw. Eng. 10, 4, 352-357.
30. WOLF, M. AND LAM, M. 1991. A data locality optimizing algorithm. In Proceedings of SIGPLAN 1991 Conference on Programming Languages Design and Implementation.
31. WOLF, M. E., MAYDAN, D. E., AND CHEN, D.-K. 1996. Combining loop transformations considering caches and scheduling. In MICRO 29. Silicon Graphics, Mountain View, CA, 274-286.
32. WOLFE, M. 1995. High Performance Compilers for Parallel Computing. Addison-Wesley, Reading, MA.