Title
A GPU-based multilevel additive schwarz preconditioner for cloth and deformable body simulation
Abstract
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.
Year
DOI
Venue
2022
10.1145/3528223.3530085
ACM Transactions on Graphics
Keywords
DocType
Volume
additive Schwarz, multilevel method, preconditioning, conjugate gradient, cloth and deformable body simulation
Journal
41
Issue
ISSN
Citations 
4
0730-0301
0
PageRank 
References 
Authors
0.34
0
3
Name
Order
Citations
PageRank
Botao Wu100.34
Zhendong Wang200.34
H. Wang374139.58