Accuracy and Stability of Numerical Algorithms
Accuracy and Stability of Numerical Algorithms
State-space truncation methods for parallel model reduction of large-scale systems
Parallel Computing - Special issue: Parallel and distributed scientific and engineering computing
Approximation of Large-Scale Dynamical Systems (Advances in Design and Control) (Advances in Design and Control)
Solving linear-quadratic optimal control problems on parallel computers
Optimization Methods & Software
Parallelizing dense and banded linear algebra libraries using SMPSs
Concurrency and Computation: Practice & Experience
Exploiting the capabilities of modern GPUs for dense matrix computations
Concurrency and Computation: Practice & Experience
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In this paper we review the effect of two high-performance techniques for the solution of matrix equations arising in control theory applications on CPU-GPU platforms, in particular advanced optimization via look-ahead and iterative refinement. Our experimental evaluation on the last GPU-generation from NVIDIA, "Kepler", shows the slight advantage of matrix inversion via Gauss-Jordan elimination, when combined with look-ahead, over the traditional LU-based procedure, as well as the clear benefits of using mixed precision and iterative refinement for the solution of Lyapunov equations.