Abstract
Large graphs involving millions of vertices are common in many practical applications and are challenging to process. To process them we present a fundamental single source shortest path (SSSP) algorithm i.e. Bellman Ford algorithm. Bellman Ford algorithm is a well known method of SSSP calculation and which is considered to be an optimization problem in the graph. SSSP problem is a major problem in the graph theory that has various applications in real world that demand execution of these algorithms in large graphs having millions of edges and sequential implementation of these algorithms takes large amount of time. In this paper, we investigates some methods which aim at parallelizing Bellman Ford Algorithm and to implement some extended or enhanced versions of this algorithm over GPU. GPU provides an application programming interface named as CUDA. CUDA is a general purpose parallel programming architecture which was introduced by Nvidia. This algorithm can reduce the execution time up to half of the basic Bellman Ford algorithm.
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