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Data structures and transformations for physically based simulation on a GPU. (English) Zbl 1323.65138
Palma, José M. Laginha M. (ed.) et al., High performance computing for computational science – VECPAR 2010. 9th international conference, Berkeley, CA, USA, June 22–25, 2010. Revised selected papers. Berlin: Springer (ISBN 978-3-642-19327-9/pbk). Lecture Notes in Computer Science 6449, 162-171 (2011).
Summary: As general purpose computing on Graphics Processing Units (GPGPU) matures, more complicated scientific applications are being targeted to utilize the data-level parallelism available on a GPU. Implementing physically-based simulation on data-parallel hardware requires preprocessing overhead which affects application performance. We discuss our implementation of physics-based data structures that provide significant performance improvements when used on data-parallel hardware. These data structures allow us to maintain a physics-based abstraction of the underlying data, reduce programmer effort and obtain \(6{\times}\)–\(8{\times}\) speedup over previously implemented GPU kernels.
For the entire collection see [Zbl 1207.68016].
MSC:
65Y10 Numerical algorithms for specific classes of architectures
68P05 Data structures
76M28 Particle methods and lattice-gas methods
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