Dynamic Task Partitioning Model in Parallel Computing

Abstract

Parallel computing systems compose task partitioning strategies in a true multiprocessing manner. Such systems share the algorithm and processing unit as computing resources which leads to highly inter process communications capabilities. The main part of the proposed algorithm is resource management unit which performs task partitioning and co-scheduling .In this paper, we present a technique for integrated task partitioning and co-scheduling on the privately owned network. We focus on real-time and non preemptive systems. A large variety of experiments have been conducted on the proposed algorithm using synthetic and real tasks. Goal of computation model is to provide a realistic representation of the costs of programming The results show the benefit of the task partitioning. The main characteristics of our method are optimal scheduling and strong link between partitioning, scheduling and communication. Some important models for task partitioning are also discussed in the paper. We target the algorithm for task partitioning which improve the inter process communication between the tasks and use the recourses of the system in the efficient manner. The proposed algorithm contributes the inter-process communication cost minimization amongst the executing processes.