Researchers presented FAME-QP, a GPU-accelerated solver for the dense quadratic programs that arise in linear model predictive control, combining constraint-dependent operator representations with fused single- and two-kernel iterations replayed through CUDA graphs. FAME-QP automatically selects its execution configuration, according to the presentation. The work targets real-time model predictive control, where solver speed on dense quadratic programs is the binding constraint.
We present FAME-QP, a GPU-accelerated solver for dense quadratic programs arising in linear model predictive control. FAME-QP combines constraint-dependent operator representations with fused single- and two-kernel iterations replayed through CUDA graphs, automatically selecting the execution config
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