FAME-QP: A GPU-Accelerated Quadratic-Programming Solver for Real-Time Model Predictive Control

Santosh Mohan Rajkumar, Debdipta Goswami, Stephanie Stockar

FAME-QP: A GPU-Accelerated Quadratic-Programming Solver for Real-Time Model Predictive Control: 4 upvotes on Hugging Face Daily Papers, #10 of 21 papers on 2026-11-12. Day-by-day upvote history.

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It had 4 upvotes by its first day, 4 upvotes by the next day, 4 upvotes by day 3, 4 upvotes by day 7, and has 4 now. It ranked #83 of 133 papers in its week and #244 of 340 in its month. Its code repository has 9 GitHub stars.

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 configuration through device calibration and problem-specific timing. It probes a cached operator bank to select the initial penalty and updates operators lazily when problem matrices change. Numerical benchmarks and simulated humanoid and quadrotor control experiments demonstrate reduced latency relative to competing GPU solvers while maintaining solution accuracy and control performance.

Paper page on Hugging Face · arXiv

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