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Recently, graph computation has emerged as an important class of high-performance computing application whose characteristics differ markedly from those of traditional, compute-bound, kernels. Libraries such as BLAS, LAPACK, and others have been successful in codifying best practices in numerical computing. The data-driven nature of graph applications necessitates a more complex application stack incorporating runtime optimization. In this paper, we present a method of phrasing graph algorithmsdoi:10.1145/2442516.2442549 dblp:conf/ppopp/EdmondsWL13 fatcat:o37koj7wkbcfzm6zlls3n63f3y