Year: 2026
Type: preprint
Abstract: We discuss the opportunities for parallelization in the recently proposed QPALM-OCP algorithm, a solver tailored to quadratic programs arising in optimal control. A significant part of the computational work can be carried out independently for the different stages in the optimal control problem. We exploit this specific structure to apply parallelization and vectorization techniques in an optimized C++ implementation of the method. Results for optimal control benchmark problems and comparisons to the original QPALM method are provided.
Source: arXiv (Cornell University)
Institutions: KU Leuven, Politecnico di Milano
Subfield: Numerical Analysis
Field: Mathematics
Domain: Physical Sciences
Open Access status: green
Awards: Beyond optimization: an algorithmic framework for structured nonmonotone inclusions, G434337789, Learning to optimize nonconvex problems: provably and efficiently, Taming Nonconvexity in Structured Low-Rank Optimization., Embedded learning and optimization for the next generation of smart industrial control systems, From model-based to data-driven: signal processing and control engineering for nonlinear systems, Innovative Algorithms for Applications on European Exascale Supercomputers
OpenAlex ID: W7135205195
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