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Scaling iterative graph computations with GraphMap
Proceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis on - SC '15
In recent years, systems researchers have devoted considerable effort to the study of large-scale graph processing. Existing distributed graph processing systems such as Pregel, based solely on distributed memory for their computations, fail to provide seamless scalability when the graph data and their intermediate computational results no longer fit into the memory; and most distributed approaches for iterative graph computations do not consider utilizing secondary storage a viable solution.doi:10.1145/2807591.2807604 dblp:conf/sc/LeeLSPZZYY15 fatcat:sxwjv6iq6beexlz5tz2qb5od5e