This project implements sparse data structures (1D sparse array and 2D sparse matrix) using doubly linked lists. Instead of storing large arrays and matrices full of zeros (wasting time and memory), ...

Abstract: Adaptive beamformer is susceptible to model mismatch, extraordinarily when the signal of interest (SOI) resides in array observation data. Different from the existing robust adaptive ...

SpMV-CNN: A set of convolutional neural nets for estimating the run time and energy consumption of the sparse matrix-vector product ...

This chapter examines the seven variants of sparse matrices implemented in the Scipy library. These seven variants include: coordinate sparse matrix, compressed sparse column matrix, compressed sparse ...

Sparse matrix computations are pivotal to advancing high-performance scientific applications, particularly as modern numerical simulations and data analyses demand efficient management of large, ...

Sparse matrix computations are prevalent in many scientific and technical applications. In many simulation applications, the solving of the sparse matrix-vector multiplication (SpMV) is critical for ...

I'm getting ready to start working on a C/C++ project that will be building and solving large tri-diagonal, block tri-diagonal and triangular matrices. I know there are a lot of libraries available ...