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The MapReduce framework has become the de-facto framework for large-scale data analysis and data mining. One important area of data analysis is graph analysis. Many graphs of interest, such as the Web graph and Social Networks, are very large in size with millions of vertices and billions of edges. To cope with this vast amount of data, researchers have been using the MapReduce framework to analyse...
The breadth-first search (BFS) is one of the most important kernels in graph theory. The Graph500 benchmark measures the performance of any supercomputer performing a BFS in terms of traversed edges per second (TEPS). Previous studies have proposed hybrid approaches that combine a well-known top-down algorithm and an efficient bottom-up algorithm for large frontiers. This reduces some unnecessary...
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