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)
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 6x-8x speedup over previously implemented GPU kernels.
Keywords:
Large Scale Simulations in CS&E, Parallel and Distributed Computing, Multiscale and Multiphysics Problems
