Document Type


Date of Award

Winter 1-31-1994

Degree Name

Master of Science in Computer Science - (M.S.)


Computer and Information Science

First Advisor

Mary M. Eshaghian

Second Advisor

Daniel Y. Chao

Third Advisor

David T. Wang


In this thesis, an implementation of a generic technique for fine grain mapping of portable parallel algorithms onto multiprocessor architectures is presented. The implemented mapping algorithm is a component of Cluster-M. Cluster-M is a novel parallel programming tool which facilitates the design and mapping of portable softwares onto various parallel systems. The other components of Cluster-M are the Specifications and the Representations. Using the Specifications, machine independent parallel algorithms are presented in a "clustered" fashion specifying the concurrent computations and communications at every step of the overall execution. The Representations, on the other hand, are a form of clustering the underlying architecture to simplify the mapping process. The mapping algorithm implemented and tested in this thesis is an efficient method for matching the Specification clusters to the Representation clusters.