Furthermore, we optimize the GPU implementation of our matrix multiplication paradigm, enhancing performance through out-of-order execution and memory management. This repository contains all the ...

-Implementation of such a parallel algorithm for multiplying a non-symmetric eleven-banded sparse matrix, represented in the compressed sparse row (CSR) format, with a dense vector is practiced on ...

A new algorithm for reducing the bandwidth and profile of a sparse matrix is described. Extensive testing on finite element matrices indicates that the algorithm typically produces bandwidth and ...

In addition, we provide an implementation of lin-RFM that scales to matrices with millions of missing entries. Our implementation is faster than the standard IRLS algorithms since it avoids forming ...

This new algorithm (IFK), when compared against well-known algorithms such as Reverse-Cuthill-McKee (RCM), Gibbs (GBS), Gibbs-Poole-Stockmeyer (GPS) and Sloan’s (SLN) over 101 test cases from the ...

Nonnegative matrix factorization (NMF), in conjunction with sparse coding, has recently been given much attention due to its part-based and easy interpretable representation. While NMF has been ...

Mathematically, the autofocusing and imaging model for sparse aperture inverse synthetic aperture radar (ISAR) has an infinite number of solutions, even with the addition of some sparsity constraints.