Global dynamic optimization problems are often represented as nonlinear optimization
problems with embedded parametric ordinary differential equations. Deterministic methods …

Many scientific and engineering applications require repeated calculations of derivatives of
output functions with respect to input parameters. Automatic Differentiation (AD) is a method …

We describe our experience porting FUN3D's CUDA-optimized kernels to Intel oneAPI
SYCL. We faced several challenges, including foremost the suboptimal performance of the …

The liberation of dust and debris particles caused by rocket plume flow from spacecraft
landing on the unprepared regolith of the Moon, Mars, and other extra-terrestrial …

Automatic differentiation (AD) is a well-known technique for evaluating analytic derivatives of
calculations implemented on a computer, with numerous software tools available for …

Automatic differentiation (AD) is ubiquitous in the training of deep neural networks and other
machine learning tasks. The emerging field of differentiable programminghas recently found …