Streamlining nonlinear programming on GPUs
Michel Schanen, François Pacaud
We propose a prototype for a vectorized modeler written in pure Julia, targeting the resolution of large-scale nonlinear optimization problems. The prototype has been designed to evaluate seamlessly the problem's expression tree with GPU accelerators. We discuss the implementation and the challenges we have encountered, as well as preliminary results comparing our prototype together with JuMP's AD backend.