2012 | OriginalPaper | Buchkapitel
Accelerating Model Reduction of Large Linear Systems with Graphics Processors
verfasst von : Peter Benner, Pablo Ezzatti, Daniel Kressner, Enrique S. Quintana-Ortí, Alfredo Remón
Erschienen in: Applied Parallel and Scientific Computing
Verlag: Springer Berlin Heidelberg
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Model order reduction of a dynamical linear time-invariant system appears in many applications from science and engineering. Numerically reliable SVD-based methods for this task require in general
$\mathcal{O}(n^3)$
floating-point arithmetic operations, with
n
being in the range 10
3
− 10
5
for many practical applications. In this paper we investigate the use of graphics processors (GPUs) to accelerate model reduction of large-scale linear systems by off-loading the computationally intensive tasks to this device. Experiments on a hybrid platform consisting of state-of-the-art general-purpose multi-core processors and a GPU illustrate the potential of this approach.