Graphs are powerful data representations used in enormous computational domains. In graph-based applications, a systematic exploration of graph such as a breath first search often is a fundamental component in the processing of the vast data sets. In this paper we prese More
Graphs are powerful data representations used in enormous computational domains. In graph-based applications, a systematic exploration of graph such as a breath first search often is a fundamental component in the processing of the vast data sets. In this paper we presented a hybrid method that in each level of processing of graph chooses the best implementation of algorithms implemented on CPU or GPU, while avoid poor performance on low and high degree graphs. Our method shows improved performance over the current state-of-the-art implementation and our results proves it.
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