Abstract

Data dependence analysis (DDA) is essential for any automatic parallelizing compiler to determine parallelizability of given portions of programs. Several techniques and tests to analyze data dependence between array elements have already been proposed. It is clear that when one examines these conventional DDA techniques, there exists a trade-off between their analysis speed and exactness of their analysis result. When the exactness of DDA is of primary importance, one can usually select the Omega test among the conventional tests. However, the Omega test analyses several ten times slower than the Banerjee test, on average. Moreover, it is hard to implement the Omega test. Therefore, in this paper a new exact test is proposed, whose algorithm is so simple that the analysis speed is generally several times faster than the Omega test. This new algorithm is mainly constructed by combining the Simplex method for linear programming with an exhaustive solution search. To evaluate this new algorithm, 55 benchmark programs were created. The comparison with the Omega test using these benchmark programs is also described

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