Sparse matrix computations are pivotal to advancing high-performance scientific applications, particularly as modern numerical simulations and data analyses demand efficient management of large ...

This paper presents an overview of the multifrontal method for the solution of large sparse symmetric positive definite linear systems. The method is formulated in terms of frontal matrices, update ...

JACOB BIEN, ROBERT J. TIBSHIRANI, Sparse estimation of a covariance matrix, Biometrika, Vol. 98, No. 4 (DECEMBER 2011), pp. 807-820 ...

A novel AI-acceleration paper presents a method to optimize sparse matrix multiplication for machine learning models, particularly focusing on structured sparsity. Structured sparsity involves a ...