CUDA-Based Parallel Preconditioning for RANS Simulations of Indoor Airflow

S. C. Kramer (), C. Pfaffenbach () and G. Lube ()
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S. C. Kramer: Institut f. Numerische und Angewandte Mathematik
C. Pfaffenbach: Institut f. Numerische und Angewandte Mathematik
G. Lube: Institut f. Numerische und Angewandte Mathematik

A chapter in Numerical Mathematics and Advanced Applications 2011, 2013, pp 663-671 from Springer

Abstract: Abstract We describe a CUDA-based parallel preconditioning method for non-normal matrices. In particular, we are interested in solving the non-isothermal Reynolds-averaged Navier-Stokes equations. These are at the bottom of indoor air-flow simulations which are necessary for predicting the energy consumption of a building configuration. Within each timestep one has to solve linearized auxiliary problems of Oseen and advection-diffusion-reaction type. Solving the linear algebraic subproblems is accelerated by CUDA by nearly an order of magnitude. Particularly suited is the sparse approximate inverse approach which yields promising results.

Keywords: Graphic Process Unit; Memory Bandwidth; Graphic Process Unit Architecture; Sparse Approximate Inverse; Oseen Problem (search for similar items in EconPapers)
Date: 2013
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-642-33134-3_70

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DOI: 10.1007/978-3-642-33134-3_70

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