Solving Algebraic Riccati Equations on Hybrid CPU-GPU Platforms
The solution of Algebraic Riccati Equations is required in many linear optimal and robust control methods such as LQR, LQG, Kalman filter, and in model order reduction techniques like the balanced stochastic truncation method. Numerically reliable algorithms for these applications rely on the sign f...
Guardado en:
| Autores principales: | , , |
|---|---|
| Formato: | Objeto de conferencia |
| Lenguaje: | Inglés |
| Publicado: |
2011
|
| Materias: | |
| Acceso en línea: | http://sedici.unlp.edu.ar/handle/10915/126121 https://40jaiio.sadio.org.ar/sites/default/files/T2011/HPC/849.pdf |
| Aporte de: |
| Sumario: | The solution of Algebraic Riccati Equations is required in many linear optimal and robust control methods such as LQR, LQG, Kalman filter, and in model order reduction techniques like the balanced stochastic truncation method. Numerically reliable algorithms for these applications rely on the sign function method, and require O(8n3) floating-point arithmetic operations, with n in the range of 103 −105 for many practical applications. In this paper we investigate the use of graphics processors (GPUs) to accelerate the solution of Algebraic Riccati Equations by off-loading the computationally intensive kernels to this device. Experiments on a hybrid platform compose by state-of-the-art general-purpose multi-core processors and a GPU illustrate the potential of this approach. |
|---|