68 citations · 68 across the 4 of their papers we have counts for
5 papers · 1 filter
ExaModels.jl: an Algebraic Modeling System for Nonlinear Programming on GPUs
Sungho Shin, Michel Schanen, François Pacaud +2
Large-scale nonlinear programs almost always exhibit partially separable and repetitive structure, yet most existing algebraic modeling systems do not take advantage of it. A nonli…
Harnessing GPU Acceleration in Large-Scale Process Optimization
Boxun Huang, David Y. Shu, Michel Schanen +3
This paper presents a proof-of-concept workflow for equation-oriented process optimization that runs entirely on a GPU. Process optimization models often incorporate complex interc…
Scalable Multi-Period AC Optimal Power Flow Utilizing GPUs with High Memory Capacities
Sungho Shin, Vishwas Rao, Michel Schanen +2
This paper demonstrates the scalability of open-source GPU-accelerated nonlinear programming (NLP) frameworks -- ExaModels.jl and MadNLP.jl -- for solving multi-period alternating…
Condensed Interior-Point Methods for Scalable Nonlinear Programming on GPUs
François Pacaud, Sungho Shin, Alexis Montoison +2
This paper explores two variants of condensed-space interior-point methods designed for GPUs - HyKKT and LiftedKKT - by analyzing their numerical properties through error analysis…
Condensed interior-point methods: porting reduced-space approaches on GPU hardware
François Pacaud, Sungho Shin, Michel Schanen +2
The interior-point method (IPM) has become the workhorse method for nonlinear programming. The performance of IPM is directly related to the linear solver employed to factorize the…