Abstract
In this paper, we present a technique to perform dependence analysis on more complex array subscripts than the linear form of the enclosing loop indices. For such complex array subscripts, we decouple the original iteration space and the dependence test iteration space and link them through index-association functions. Dependence analysis is performed in the dependence test iteration space to determine whether the dependence exists in the original iteration space. The dependence distance in the original iteration space is determined by the distance in the dependence test iteration space and the property of index-association functions. For certain non-linear expressions, we show how to equivalently transform them to a set of linear expressions. The latter can be used in traditional dependence analysis techniques targeting subscripts which are linear forms of enclosing loop indices. We also show how our advanced dependence analysis technique can help parallelize some otherwise hard-to-parallelize loops.
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References
Blume, W., Eigenmann, R.: Non-linear and symbolic data dependence testing. IEEE Transactions of Parallel and Distributed Systems 9(12), 1180–1194 (1998)
Feautrier, P.: Dataflow analysis of array and scalar references. Journal of Parallel Programming 20(1), 23–53 (1991)
Goff, G., Kennedy, K., Tseng, C.-W.: Practical dependence testing. In: Proceedings of the ACM SIGPLAN 1991 Conference on Programming Language Design and Implementation, Toronto, Ontario, Canada, June 1991, pp. 15–29 (1991)
Haghighat, M., Polychronopoulos, C.: Symbolic analysis for parallelizing compilers. ACM Transactions on Programming Languages and Systems 18(4), 477–518 (1996)
Hoeflinger, J., Paek, Y.: The access region test. In: Carter, L., Ferrante, J. (eds.) LCPC 1999. LNCS, vol. 1863, p. 271. Springer, Heidelberg (1999)
Maydan, D., Hennessy, J., Lam, M.: Efficient and exact data dependence analysis. In: Proceedings of ACM SIGPLAN Conference on Programming Language Design and Implementation, Toronto, Ontario, Canada, June 1991, pp. 1–14 (1991)
Moon, S., Hall, M.: Evaluation of predicated array data-flow analysis for automatic parallelization. In: Proceedings of ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming, Atlanta, GA, May 1999, pp. 84–95 (1999)
Pugh, W.: A practical algorithm for exact array dependence analysis. Communications of the ACM 35(8), 102–114 (1992)
Song, Y., Li, Z.: New tiling techniques to improve cache temporal locality. In: Proceedings of ACM SIGPLAN Conference on Programming Language Design and Implementation, Atlanta, GA, May 1999, pp. 215–228 (1999)
Standard Performance Evaluation Corporation. The SPEC CPU2000 benchmark suite, http://www.specbench.org
Sun Microsystems, Inc., Sun ONE Studio 8 Compiler Collection, http://docs.sun.com
Wolf, M.: Improving Locality and Parallelism in Nested Loops. PhD thesis, Department of Computer Science, Stanford University (August 1992)
Wolfe, M. (ed.): High Performance Compilers for Parallel Computing. Addison- Wesley Publishing Company, Reading (1995)
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Song, Y., Kong, X. (2004). Index-Association Based Dependence Analysis and its Application in Automatic Parallelization. In: Rauchwerger, L. (eds) Languages and Compilers for Parallel Computing. LCPC 2003. Lecture Notes in Computer Science, vol 2958. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-24644-2_15
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DOI: https://doi.org/10.1007/978-3-540-24644-2_15
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-21199-0
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