High-performance matrix multiplication remains a cornerstone of numerical computing, underpinning a wide array of applications from scientific simulations to machine learning. Researchers continually ...

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

A new technique that efficiently retrieves scattered light from fluorescent sources can be used to record neuronal signals coming from deep within the brain. The technique, developed by physicists at ...

This article demonstrates a fast and practical procedure for the maximum likelihood estimation of models with spatial interaction on a lattice, such as Gaussian Markov random fields (conditional ...

In the early 2000s, digital signal processors (DSP) were simple in architecture and limited in performance, but complex in programming. However, they evolved to meet of the increased performance ...