Partitioning Techniques for Large-Grained Parallelism

Rakesh Agrawal, H. V. Jagadish

Abstract: A model is presented for parallel processing in loosely coupled multiprocessing environments, such as networks of computer workstations, that are amenable to large-grained parallelism. The model takes into account the overhead involved in data communication to and from a remote processor and can be used to partition a large class of computations optimally, consisting of computations that can be organized as a one-level tree and are homogeneous and separable. The optimal partition can be determined for a given number processors, and, if required, the optimal number of processors to use can also be derived. Experimental results validate the model and demonstrate its effectiveness.<