1 citations · 1 across the 7 of their papers we have counts for
9 papers
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…
An Augmented Lagrangian Method on GPU for Security-Constrained AC Optimal Power Flow
François Pacaud, Armin Nurkanović, Anton Pozharskiy +2
We present a new algorithm for solving large-scale security-constrained optimal power flow in polar form (AC-SCOPF). The method builds on Nonlinearly Constrained augmented Lagrangi…
Modeling and Optimization of Control Problems on GPUs
Alexis Montoison, Jean-Baptiste Caillau
We present a fully Julia-based, GPU-accelerated workflow for solving large-scale sparse nonlinear optimal control problems. Continuous-time dynamics are modeled and then discretize…
Harnessing Batched BLAS/LAPACK Kernels on GPUs for Parallel Solutions of Block Tridiagonal Systems
David Jin, Alexis Montoison, Sungho Shin
Block-tridiagonal systems are prevalent in state estimation and optimal control, and solving these systems is often the computational bottleneck. Improving the underlying solvers t…
GPU Implementation of Second-Order Linear and Nonlinear Programming Solvers
Alexis Montoison, François Pacaud, Sungho Shin +1
In recent years, GPU-accelerated optimization solvers based on second-order methods (e.g., interior-point methods) have gained momentum with the advent of mature and efficient GPU-…
Revisiting Sparse Matrix Coloring and Bicoloring
Alexis Montoison, Guillaume Dalle, Assefaw Gebremedhin
Sparse matrix coloring and bicoloring are fundamental building blocks of sparse automatic differentiation. Bicoloring is particularly advantageous for rectangular Jacobian matrices…
Recovering sparse DFT from missing signals via interior point method on GPU
Wei Kuang, Alexis Montoison, Vishwas Rao +2
We propose a method to recover the sparse discrete Fourier transform (DFT) of a signal that is both noisy and potentially incomplete, with missing values. The problem is formulated…
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…
Batched Second-Order Adjoint Sensitivity for Reduced Space Methods
François Pacaud, Michel Schanen, Daniel Adrian Maldonado +4
This paper presents an efficient method for extracting the second-order sensitivities from a system of implicit nonlinear equations on upcoming graphical processing units (GPU) dom…