Lonestar: A suite of parallel irregular programs


Until recently, parallel programming has largely focused on the exploitation of data-parallelism in dense matrix programs. However, many important application domains, including meshing, clustering, simulation, and machine learning, have very different algorithmic foundations: they require building, computing with, and modifying large sparse graphs. In the… (More)
DOI: 10.1109/ISPASS.2009.4919639
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