3 papers
math.OC2026
Disciplined Nonlinear Programming
Daniel Cederberg, William Zhang, Parth Nobel +1
We introduce disciplined nonlinear programming (DNLP), a syntax for specifying nonlinear programming problems. DNLP is inspired by disciplined convex programming (DCP) and allows s…
math.OC2025
CuClarabel: GPU Acceleration for a Conic Optimization Solver
Yuwen Chen, Danny Tse, Parth Nobel +2
We present the GPU implementation of the general-purpose interior-point solver Clarabel for convex optimization problems with conic constraints. We introduce a mixed parallel compu…
math.OC2025
Differentiating Through a Quadratic Cone Program
Quill Healey, Parth Nobel, Stephen Boyd
Quadratic cone programs are rapidly becoming the standard canonical form for convex optimization problems. In this paper we address the question of differentiating the solution map…