MPC toolbox with GPU accelerated optimization algorithms. The introduction of Graphical Processing Units (GPUs) in scienti c computing has shown great promise in many di erent elds. While GPUs are capable of very high oating point performance and memory bandwidth, its massively parallel architecture requires algorithms to be reimplemented to suit the di erent architecture. Interior point method can be used to solve convex optimization problems. These problems often arise in elds such as in Model Predictive Control (MPC), which may have real-time requirements for the solution time. This paper presents a case study in which we utilize GPUs for a Linear Programming Interior Point Method to solve a test case where a series of power plants must be controlled to minimize the cost of power production. We demonstrate that using GPUs for solving MPC problems can provide a speedup in solution time.
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- Ploskas, Nikolaos; Samaras, Nikolaos: Efficient GPU-based implementations of simplex type algorithms (2015)