Abstract
Loop parallelization is an important issue in the acceleration of the execution of scientific programs. To exploit parallelism in loops a system of equations representing the dependencies between the loop iterations and a system of non-equations indicating the loop boundary conditions has to be solved. This is a NP-Complete problem. Our major contribution in this paper has been to apply genetic algorithm to solve system of equation and non-equation resulted from loop dependency analysis techniques to find two dependent loop iterations. We use distance vector to find the rest of dependencies.
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Parsa, S., Lotfi, S. A New Approach to Parallelization of Serial Nested Loops Using Genetic Algorithms. J Supercomput 36, 83–94 (2006). https://doi.org/10.1007/s11227-006-3557-4
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DOI: https://doi.org/10.1007/s11227-006-3557-4