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This work was funded as part of Google Summer of Code over 3 summers, 2 of which were for Abhinav Mehndiratta and the last of which was for William Kimmerer.
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Fast sparse linear algebra is an essential part of the scientific computing toolkit. Outside of the usual applications, like differential equations, sparse linear algebra provides an elegant way to express graph algorithms on adjacency and incidence matrices. The GraphBLAS standard specifies a set of operations for computing sparse matrix graph algorithm in a vein similar to the BLAS or LAPACK standards.
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SuiteSparseGraphBLAS.jl is a blazing fast package for shared memory sparse matrix operations which wraps Tim Davis' SuiteSparse:GraphBLAS implementation of the GraphBLAS C specification.
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SuiteSparseGraphBLAS.jl is a blazing fast package for shared memory sparse matrix operations which wraps Tim Davis' SuiteSparse:GraphBLAS. If you use this package in your research please see [Citing](@ref).
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