Accelerated kerninghan lin algorithm for graph partitioning

Grouping the vertex of the graph into sets of certain sizes such that minimum number of edges cross between the sets is called graph partitioning. This NP (Non-deterministic Polynomial time)-complete problem has important applications in computing, task scheduling, and parallel processing. We are implementing Kernighan-Lin, a local algorithm on both a Central Processing Unit (CPU) and a Graphics Processing Unit (GPU) system. The implementation in CPU is done in C language whereas GPU implementation is done in CUDAC. The CPU implementation of KL-algorithm has a complexity of O(n
³
). To overcome such a large complexity we are recognizing steps that can be done in parallel, thereby implementing in GPU. GPU has a highly parallel architecture consisting of thousands of cores. These small, efficient cores are constructed in such a way that they can handle multiple task concurrently. Thus, implementation in GPU reduces the complexity to O(n).