Heuristics for Symmetric Rectilinear Matrix Partitioning

29 Dec 2019 Yaşar Abdurrahman Çatalyürek Ümit V.

Partitioning sparse matrices and graphs is a common and important problem in many scientific and graph analytics applications. In this work, we are concerned with a spatial partitioning called rectilinear partitioning (also known as generalized block distribution) of sparse matrices, which is needed for tiled (or {\em blocked}) execution of sparse matrix and graph analytics kernels... (read more)

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  • DATA STRUCTURES AND ALGORITHMS