Driven by deep learning, there has been a surge of specialized processors for matrix
multiplication, referred to as Tensor Core Units (TCUs). These TCUs are capable of …

In this paper, we present a scalable, numerically stable, high-performance tridiagonal solver.
The solver is based on the SPIKE algorithm for partitioning a large matrix into small …

Computer vision and pattern recognition systems play an important role in our lives by
means of automated face detection, face and gesture recognition, and estimation of gender …

This paper documents development of a multiple‐Graphics Processing Unit (GPU) version
of FUNWAVE‐Total Variation Diminishing (TVD), an open‐source model for solving the fully …

There are some quasi-tridiagonal system of linear equations arising from numerical
simulations, and some solving algorithms encounter great challenge on solving quasi …

The solving of tridiagonal systems is one of the most computationally expensive parts in
many applications, so that multiple studies have explored the use of NVIDIA GPUs to …

When the oil and gas extraction in a well is over or ended by wellbore issues, a Plugging
and Abandoning (P&A) operation is required. The usual method is the well cementation. A …

In this paper we propose and evaluate a set of new strategies for the solution of three
dimensional separable elliptic problems on CPU–GPU platforms. The numerical solution of …

Commodity many-core hardware is now mainstream, but parallel programming models are
still lagging behind in efficiently utilizing the application parallelism. There are (at least) two …

The solving of tridiagonal systems is one of the most computationally expensive parts in
many applications, so that multiple studies have explored the use of NVIDIA GPUs to …