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Cycles count in a graph is an NP-complete problem. This paper minimizes the execution time to solve the problem compared to the other traditional serial, CPU based one. It reduces the hardware resources needed to a single commodity GPU. The authors developed an algorithm to approximate counting the number of cycles in an undirected graph, by utilizing a modern parallel computing paradigm called CUDA (Compute Unified Device Architecture) from nVIDIA, using the capabilities of the massively parallel multi-threaded specialized processor called Graphics Processing Unit (GPU). The algorithm views the graph from combinatorial perspective rather than the traditional adjacency matrix/list view.
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