Data Structures and Transformations for Physically Based Simulation on a GPU
Perhaad Mistry (Northeastern University)
Dana Schaa (Northeastern University)
Byunghyun Jang (Northeastern University)
David Kaeli (Northeastern University)
Albert Dvornik (Simquest LLC)
Dwight Meglan (Simquest LLC)
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 6x-8x speedup over previously implemented GPU kernels.
Large Scale Simulations in CS&E, Parallel and Distributed Computing, Multiscale and Multiphysics Problems