Data structures and transformations for physically based simulation on a GPU

Authors:
Perhaad Mistry;Dana Schaa;Byunghyun Jang;David Kaeli;Albert Dvornik;Dwight Meglan
Affiliations:
Department of Electrical and Computer Engineering, Northeastern University, Boston, MA;Department of Electrical and Computer Engineering, Northeastern University, Boston, MA;Department of Electrical and Computer Engineering, Northeastern University, Boston, MA;Department of Electrical and Computer Engineering, Northeastern University, Boston, MA;Simquest LLC, Boston, MA;Simquest LLC, Boston, MA
Venue:
VECPAR'10 Proceedings of the 9th international conference on High performance computing for computational science
Year:
2010

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Abstract

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×-8× speedup over previously implemented GPU kernels.