An efficient k-way graph partitioning algorithm for task allocation in parallel computing systems

Abstract

The k-way graph partitioning problem can be transformed into the maximum k-cut problem using a proposed technique of graph modification. It is possible to transform the graph partitioning problem into the max-cut problem by incorporating node size information into the edge weight. After transformation, a very simple cost function can be devised which makes the proposed algorithm more efficient than the Kernighan-Lin (K-L) algorithm (1970). The computing time per iteration of the algorithm is O(k*N/sup 2/), where N is the number of nodes in the given graph. Experimental results show that the proposed algorithm outperforms the K-L algorithm both in the quality of solutions and in the elapsed time. Also, as the difference between the sizes of the nodes increases, the performance gap between the proposed algorithm and the K-L algorithm becomes larger.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>