Abstract
Lyapack is a package for the solution of large-scale sparse problems arising in control theory. The package has a modular design, and is implemented as a Matlab toolbox, which renders it easy to utilize, modify and extend with new functionality. However, in general, the use of Matlab in combination with a general-purpose multi-core architecture (CPU) offers limited performance when tackling the sparse linear algebra operations underlying the numerical methods involved in control theory. In this paper we extend Lyapack to leverage the computational power of graphics processors (GPUs). The experimental evaluation of a new CUDA-enabled solver for the Lyapunov equation, a crucial operation appearing in control theory problems, shows a significant runtime reduction when compared with the original CPU version of Lyapack, while retaining the usability of a Matlab-based implementation.
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