A GPU-Based Multilevel Additive Schwarz Preconditioner for Cloth and Deformable Body Simulation

In this paper, we wish to push the limit of real-time cloth and deformable body simulation to a higher level with 50K to 500K vertices, based on the development of a novel GPU-based multilevel additive Schwarz (MAS) pre-conditioner. Similar to other preconditioners under the MAS framework, our preconditioner naturally adopts multilevel and domain decomposition concepts. But contrary to previous works, we advocate the use of small, non-overlapping domains that can well explore the parallel computing power on a GPU. Based on this idea, we investigate and invent a series of algorithms for our preconditioner, including multilevel domain construction using Morton codes, low-cost matrix precomputation by one-way Gauss-Jordan elimination, and conflict-free symmetric-matrix-vector multiplication in runtime preconditioning. The experiment shows that our preconditioner is effective, fast, cheap to precompute and scalable with respect to stiffness and problem size. It is compatible with many linear and nonlinear solvers used in cloth and deformable body simulation with dynamic contacts, such as PCG, accelerated gradient descent and L-BFGS. On a GPU, our preconditioner speeds up a PCG solver by approximately a factor of four, and its CPU version outperforms a number of competitors, including ILU0 and ILUT.

Automated summary

This paper introduces a novel GPU-based multilevel additive Schwarz (MAS) preconditioner for real-time cloth and deformable body simulation. By using small, non-overlapping domains and a series of algorithms for matrix computation, the preconditioner is scalable with respect to stiffness and problem size, compatible with various solvers, and outperforms competitors in terms of performance.