Many-core acceleration for model predictive control systems

This paper proposes a novel many-core execution strategy for real-time model predictive controls. The key idea is to exploit predicted input values, which are produced by the model predictive control itself, to speculatively solve an op- timal control problem. It is well known that control appli- cations are not suitable for multi- or many-core processors, because feedback-loop systems inherently stand on sequen- tial operations. Since the proposed scheme does not rely on conventional thread-/data-level parallelism, it can be easily applied to such control systems. An analytical evaluation using a real application demonstrates the potential of per- formance improvement achieved by the proposed speculative executions.