Derivatives play a critical role in computational statistics, examples being Bayesian
inference using Hamiltonian Monte Carlo sampling and the training of neural networks …

Abstract deal. II is a state-of-the-art finite element library focused on generality, dimension-
independent programming, parallelism, and extensibility. Herein, we outline its primary …

SUMMARY A rigorous computational framework for the dimensional reduction of discrete,
high‐fidelity, nonlinear, finite element structural dynamics models is presented. It is based …

There are several AD tools available that all implement different strategies for the reverse
mode of AD. The most common strategies are primal value ta** (implemented eg by …

Gradient-based optimization problems are encountered in many fields, but the associated
task of differentiating large computer algorithms can be formidable. The operator …

The application of peridynamics for engineering analysis requires an efficient and robust
software implementation. Key elements include processing of the discretization, the …

This paper describes a new parallel, scalable and robust finite element based solver for the
first-order Stokes momentum balance equations for ice flow. The solver, known as …

Albany is a multiphysics code constructed by assembling a set of reusable, general
components. It is an implicit, unstructured grid finite element code that hosts a set of …

The computational solution of the governing balance equations for mass, momentum, heat
transfer and magnetic induction for resistive magnetohydrodynamics (MHD) systems can be …

Exascale computing systems are essential for the scientific fields that will transform the 21st
century global economy, including energy, biotechnology, nanotechnology, and materials …