A condensed-space interior-point method factorized on GPU/SIMD hardware solves constrained LQ-MPC problems an order of magnitude faster than CPU when the number of inputs is small and the horizon moderate.
HPIPM: a high-performance quadratic programming framework for model predictive control
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Exploiting GPU/SIMD Architectures for Solving Linear-Quadratic MPC Problems
A condensed-space interior-point method factorized on GPU/SIMD hardware solves constrained LQ-MPC problems an order of magnitude faster than CPU when the number of inputs is small and the horizon moderate.