9317301 Prasanna Future parallel processing systems will consist of diverse high performance computers integrated to form a Heterogeneous Computing Network that allows them to cooperate in solving complex scientific and engineering problems. Each machine connected to the network may be suitable for a different class of parallel computations. Such an organization will exploit the current advances in parallel hardware architectures, interconnection technologies, and programming paradigms to provide a cost-effective environment for high performance parallel computing. Efficient utilization of such an environment depends on a number of issues to be addressed including techniques to partition application tasks and map the subtasks onto various machines in the network. This research addresses several key issues in using a heterogeneous computing environment. The work will focus on modeling the Heterogeneous Computing paradigm for algorithm development, addressing the computational issues involved in using such a paradigm, design of partitioning and mapping strategies, and integrating these strategies into existing programming systems to solve computationally demanding problems in image understanding. ***
