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.

SIAM Journal on Numerical Analysis, Vol. 12, No. 4 (Sep., 1975), pp. 617-629 (13 pages) The method of conjugate gradients for solving systems of linear equations with a symmetric positive definite ...

This newly developed data processing utilizes computing and communications technologies that leverage “sparse matrix” data structures in order to significantly accelerate the performance of vector ...

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 ...

We introduce a constrained empirical loss minimization framework for estimating highdimensional sparse precision matrices and propose a new loss function, called the D-trace loss, for that purpose. A ...

The company said its vector processor, called the Aurora Vector Engine, leverages “sparse matrix” data structures to accelerate processor performance in executing machine learning tasks.