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arXiv · 2510.03932

Modeling and Optimization of Control Problems on GPUs

Alexis Montoison·Jean-Baptiste Caillau
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Abstract

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 discretized via direct transcription with \texttt{OptimalControl.jl} into structured sparse nonlinear programs. These programs are compiled into GPU kernels using \texttt{ExaModels.jl}, leveraging SIMD parallelism for fast evaluation of objectives, constraints, gradients, Jacobians and Hessians. The resulting sparse problems are solved entirely on GPU using the interior-point solver \texttt{MadNLP.jl} and the GPU sparse linear solver cuDSS, yielding significant speed-ups over CPU-based approaches.

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Alexis Montoison, Jean-Baptiste Caillau. 2025-10-04. Modeling and Optimization of Control Problems on GPUs. https://arxiv.org/abs/2510.03932

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