{"ID":2860689,"CreatedAt":"2026-06-01T04:54:23.091178241Z","UpdatedAt":"2026-06-01T04:54:23.091178241Z","DeletedAt":null,"paper_url":"https://arxiv.org/abs/2510.03932","arxiv_id":"2510.03932","title":"Modeling and Optimization of Control Problems on GPUs","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.","short_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 k...","url_abs":"https://arxiv.org/abs/2510.03932","url_pdf":"https://arxiv.org/pdf/2510.03932v2","authors":"[\"Alexis Montoison\",\"Jean-Baptiste Caillau\"]","published":"2025-10-04T20:24:58Z","proceeding":"math.OC","tasks":"[\"math.OC\"]","methods":"[]","has_code":false}