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This paper investigates how to improve the memory locality of graph-structured analytics on large-scale shared memory systems. We demonstrate that a graph partitioning where all in-edges for a vertex are placed in the same partition improves memory locality. However, realising performance improvement through such graph partitioning poses several challenges and requires rethinking the classification of graph algorithms and preferred data structures. We introduce the notion of medium-densedoi:10.1109/icpp.2017.27 dblp:conf/icpp/SunVN17 fatcat:zzr7aonlwzbxrkqlk4kcfme2gy