In sparse matrices, zero values can be discarded from storage or computations to accelerate execution. In order to represent only non-zero values in sparse matrices, the cuSPARSE library supports ...

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 ...

This project is a Python-based application to handle sparse matrices efficiently. Sparse matrices are data structures where most of the elements are zeros. By only storing non-zero values, this ...

Improving on this has been an open problem even for sparse linear systems with poly (n) condition number. In this paper, we present an algorithm that solves linear systems in sparse matrices ...

Decomposing sparse matrices into lower and upper triangular matrices (sparse LU factorization) is a key operation in many computational scientific applications. We developed SparseLU, a sparse linear ...

To this end, we introduce a co-sparse non-negative matrix factorization method to high-dimensional data by simultaneously imposing sparsity in both two decomposed matrices.