Which solver to choose depends on the nature of your matrix. SuiteSparse is built on top of LAPACK and BLAS, which are pretty low level and FORTRAN-y.

In particular, we extend the DBCSR sparse matrix library, which is the basic building block for linear scaling electronic structure theory and low scaling correlated methods in CP2K. The library is ...

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 ...

This paper considers estimation of sparse covariance matrices and establishes the optimal rate of convergence under a range of matrix operator norm and Bregman divergence losses. A major focus is on ...

Real PIM systems can provide high levels of parallelism, large aggregate memory bandwidth and low memory access latency, thereby being a good fit to accelerate the widely-used, memory-bound Sparse ...

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