Optimizing Sparse Linear Algebra for Large-Scale Graph Analytics

Daniele Buono, John A. Gunnels, Xinyu Que, Fabio Checconi, Fabrizio Petrini, Tai-Ching Tuan, Chris Long

Abstract: Emerging data-intensive applications attempt to process and provide insight into vast amounts of online data. A new class of linear algebra algorithms can efficiently execute sparse matrix-matrix and matrix-vector multiplications on large-scale, shared memory multiprocessor systems, enabling analysts to more easily discern meaningful data relationships, such as those in social networks.