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dc.contributor.authorKepner, Jeremy
dc.contributor.authorBader, David A.
dc.contributor.authorDavis, Tim
dc.contributor.authorPearce, Roger
dc.contributor.authorWolf, Michael M.
dc.date.accessioned2022-11-09T02:18:45Z
dc.date.available2022-11-09T02:18:45Z
dc.date.issued2022-11-09
dc.identifier.urihttps://hdl.handle.net/1721.1/146227
dc.description.abstractThe challenges associated with graph algorithm scaling led multiple scientists to identify the need for an abstraction layer that would allow algorithm specialists to write high-performance, matrix-based graph algorithms that hardware specialists could then design to without having to manage the complexities of every type of graph algorithm. With this philosophy in mind, a number of researchers (including two Turing Award winners) came together and proposed the idea that “the state of the art in constructing a large collection of graph algorithms in terms of linear algebraic operations is mature enough to support the emergence of a standard set of primitive building blocks”en_US
dc.language.isoen_USen_US
dc.relation.ispartofseriesSIAM News
dc.rightsAttribution-NoDerivs 3.0 United States*
dc.rights.urihttp://creativecommons.org/licenses/by-nd/3.0/us/*
dc.subjectLinear Algebraen_US
dc.subjectGraph Algorithmsen_US
dc.titleGraphBLAS and GraphChallenge Advance Network Frontiersen_US
dc.typeArticleen_US


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    News articles about the LLSC and programs that are supported by the LLSC

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