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arXiv · 2505.12078

GPU-Accelerated SPOCK for Scenario-Based Risk-Averse Optimal Control Problems

Ruairi Moran·Pantelis Sopasakis
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Abstract

This paper presents a GPU-accelerated implementation of the SPOCK algorithm, a proximal method designed for solving scenario-based risk-averse optimal control problems. The proposed implementation leverages the massive parallelization of the SPOCK algorithm, and benchmarking against state-of-the-art interior-point solvers demonstrates GPU-accelerated SPOCK's competitive execution time and memory footprint for large-scale problems. We further investigate the effect of the scenario tree structure on parallelizability, and so on solve time.

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Ruairi Moran, Pantelis Sopasakis. 2025-05-17. GPU-Accelerated SPOCK for Scenario-Based Risk-Averse Optimal Control Problems. https://arxiv.org/abs/2505.12078

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