In this paper, we evaluate the suitability of the Tegra X1 processor as a platform for embedded model predictive control. MPC relies on the real time solution ...
[PDF] Efficient Convex Optimization on GPUs for Embedded Model ...
www.merl.com › publications › docs
Feb 5, 2017 , In this paper, we evaluate the suitability of the Tegra X1 processor as a platform for embedded model pre- dictive control. MPC relies on the ...
Efficient convex optimization on gpus for embedded model predictive control. Published in the General Purpose GPUs ACM 2017, 2017.
Feb 5, 2017 , In this section we will briefly describe MPC, the PQP and ADMM algorithms, as well as GPU computing. 2.1 Model Predictive Control. Linear MPC is ...
, "Efficient Convex Optimization on GPUs for Embedded Model Predictive Control", Workshop on General Purpose Processing with Graphics Processing Units, DOI ...
... GPU-based computational techniques as efficient building blocks for their convex optimization code. xiv. Page 15. CHAPTER 1. INTRODUCTION. Optimization is a ...
Jun 14, 2022 , This paper proposes a graphics processing unit (GPU)-based method to parallelize and accelerate PD-IPM for real-time MPC. The real-time ...
People also ask
What are convex optimization methods?
Is convex optimization useful?
What are the applications of convex optimization?
How is convex optimization used in machine learning?
This work addresses the implementation of an interior point algorithm for the solution of multi-stage quadratic programming (QP) problems. Of particular ...
Missing: GPUs | Show results with:GPUs
Nov 29, 2023 , Model-predictive control (MPC) is a widely used control strategy that solves a receding-horizon optimization problem while reasoning about ...
Efficient Convex Optimization on GPUs for Embedded Model Predictive Control. Leiming Yu; Abraham Goldsmith; Stefano Di Cairano. Merge or Separate?: Multi-job ...