Sparse matrix-vector multiplication (SpMV) is the most important kernel in parallel iterative method for solving modified equation in large scale power system power flow calculation. In this paper, ...

Sparse Matrix Compression efficiently stores and manages sparse matrices using linked lists and arrays. It supports insertion, deletion, search, updates, and CSV-based storage while optimizing memory ...

Implementation of sparse matrices in C language, where a matrix is represented using Linked Lists. A sparse matrix is a matrix in which most of the elements are zero. By only storing non-zero elements ...

Here a massively parallel medium sparse matrix-matrix multiplication algorithm is designed for first-principle calculations and implemented on the new-generation Sunway supercomputer. Experiments show ...

However, it might be more reasonable to require both W and H are sparse when trying to learn useful features from a database of images. In this paper, we propose a co-sparse non-negative matrix ...

Discover how our paper utilizes a sparse lasso penalized D-trace loss to estimate high-dimensional precision matrices, achieving positive-definiteness and sparsity. Learn about our efficient ...

A new algorithm is presented for the calculation of the ladder-type term of the coupled cluster singles and doubles (CCSD) equations using two-electron integrals in atomic orbital (AO) basis. The ...