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Subgraph matching is a key operation on graph data. Social network (SN) providers may want to find all subgraphs within their social network that "match" certain query graph patterns. Unfortunately, subgraph matching is NP-complete, making its application to massive SNs a major challenge. Past work has shown how to implement subgraph matching on a single processor when the graph has 10-25M edges. In this paper, we show how to use cloud computing in conjunction with such existing singledoi:10.1109/asonam.2010.80 dblp:conf/asunam/BrochelerPS10 fatcat:hh2w6zpgnfbz7ffd3bitkymwsi