A. Graph Partitioning based Methodologies Graph partitioning techniques view the task as a task graph where the vertices represent the task modules and edges represent the communication between those tasks. Load balancing is a process which with the help of inter-node communication produce equal partltIOns of the task graph. The number of partitions depends on the number of processing elements and their topology in the processor graph. Some factors that are involved in selecting the number of partitions are Load balancing and Communication cost. The graph bisection problem has been studied in the past by many authors (see, e.g., [5], [6]) in the context of graph theory as well as VLSI circuit layout which are NP hard problems. Most of the graph bisection methods, therefore, seek a good approximation to the optimal partitioning that can be calculated efficiently. Some already proposed algorithms are Recursive graph bisection (RGB) algorithm [6] and KL (Kernighan-Lin) algorithm ([8], [9]). Different techniques like matching parallel process to a hypercube and spectral bisection have been pursued in [10], [11 ], [12]. However, our research focuses primarily on the problem of task assignment using parallel graph matching.