On automatic parallelization of irregular reductions on scalable shared memory systems

This paper presents a new parallelization method for reductions of arrays with subscripted subscripts on scalable shared-memory multiprocessors. The mapping of computations is based on the conflict-free write distribution of the reduction vector across the processors. The proposed method is general, scalable, and easy to implement on a compiler. A performance evaluation and comparison with other existing techniques is presented. From the experimental results, the proposed method is a clear alternative to the array expansion and privatized buffer methods, usual on state-of-the-art; parallelizing compilers, like Polaris or SUIF.