IEEE Transactions on Computers
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In this work we address the problem of scheduling loops with dependences in the context of speculative parallelization. We show that scheduling alternatives are highly influenced by the dependence violation pattern presented in the code. We center our analysis in those algorithms where dependences are less likely to appear as the execution proceeds, like incremental randomized algorithms. These algorithms are, in general, hard to parallelize by hand, and represent a challenge for any automatic parallelization scheme. Our analysis led us to the development of MESETA, a new scheduling strategy that takes into account the probability of a dependence violation to determine the number of iterations being scheduled.MESETA is compared, among others, with Fixed-Size Chunking (FSC), the only scheduling alternative used so far in the context of speculative parallelization. Our experimental results show a 3% to 22% speedup improvement over FSC for the same incremental randomized algorithm.