Partitioning Techniques for Large-Grained Parallelism

  • Authors:
  • R. Agrawal;H. V. Jagadish

  • Affiliations:
  • AT&T Bell Laboratories, Murray Hill, NJ;AT& Bell Laboratories, Murray Hill, NJ

  • Venue:
  • IEEE Transactions on Computers
  • Year:
  • 1988

Quantified Score

Hi-index 14.98

Visualization

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.