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Parallel implicit time integration for particle-based models on graphics clusters

Particle-based models are widely spread in the field of computer graphics, and mainly used for real-time simulations of soft deformable bodies. One of the high-demanding computational components of such physically-based simulations is numerical time integration. As the size of the models increases, this component becomes a potential bottleneck in the simulation process, thus parallelism must be deployed in order to preserve the real-time attribute. This paper presents an approach to parallel implicit numeric time integration for graphics clusters. To deal with very large models, we employ a static domain decomposition approach and we fully utilize the massively data parallel capabilities of GPU clusters. We discuss the parallel conjugate gradient algorithm used for time integration and we present a parallel method for generating the very large sparse matrices and vectors involved.