The computation of the singular value decomposition, or SVD, has a long history with many
improvements over the years, both in its implementations and algorithmically. Here, we …

This chapter presents the current best design and implementation practices for the
acceleration of dense linear algebra (DLA) on GPUs. Examples are given with fundamental …

Gaussian elimination is a canonical linear algebra procedure for solving linear systems of
equations. In the last few years, the algorithm has received a lot of attention in an attempt to …

We apply the tensor train (TT) decomposition to construct the tensor product polynomial
chaos expansion (PCE) of a random field, to solve the stochastic elliptic diffusion PDE with …

We present a method of reasoning directly about functional programs in Second-Order
Logic, based on the use of explicit second-order definitions for inductively defined data …

The solution of (generalized) eigenvalue problems for symmetric or Hermitian matrices is a
common subtask of many numerical calculations in electronic structure theory or materials …

Determinantal point processes (DPPs) were introduced by Macchi (Macchi 1975 Adv. Appl.
Probab. 7, 83–122) as a model for repulsive (fermionic) particle distributions. But their recent …

We introduce a new singular value decomposition (SVD) solver based on the QR-based
Dynamically Weighted Halley (QDWH) algorithm for computing the partial spectrum SVD …

This work evaluated the use of OpenMP tasking with target GPU offloading as a potential
solution for programming productivity and performance on heterogeneous systems. Also, it …

The LU factorization is an important numerical algorithm for solving systems of linear
equations in science and engineering and is a characteristic of many dense linear algebra …