ODCHP: a new effective mechanism to maximize parallelism of nested loops with non-uniform dependences

Abstract

There are many methods for nested loop partitioning. However, most of them perform poorly when partitioning loops with nonuniform dependences. This paper proposes a generalized and optimized loop partitioning mechanism to exploit parallelism from nested loops with non-uniform dependences. Our approach, based on dependence convex theory, will divide the loop into variable size partitions. Furthermore, the proposed algorithm partitions a nested loop by using the copy-renaming and the optimized partitioning techniques to minimize the number of parallel regions of the iteration space. Consequently, it outperforms the previous partitioning mechanisms of nested loops with non-uniform dependences. Many optimization techniques are used to reduce the complexity of the algorithm. Compared with other popular techniques, our scheme shows a dramatic improvement in the preliminary performance results. (C) 2001 Elsevier Science Inc. All rights reserved.