collaborators

7 papers

cs.MS2025

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…

math.OC2025

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-…

math.OC2025

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…

math.OC2025

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…

math.OC2025

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…

math.NA2025

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…