Vertex Block Descent

Author:

Chen Anka He1ORCID,Liu Ziheng1ORCID,Yang Yin1ORCID,Yuksel Cem12ORCID

Affiliation:

1. Kahlert School of Computing, University of Utah, Salt Lake City, Utah, United States of America

2. Roblox, Salt Lake City, Utah, United States of America

Abstract

We introduce vertex block descent, a block coordinate descent solution for the variational form of implicit Euler through vertex-level Gauss-Seidel iterations. It operates with local vertex position updates that achieve reductions in global variational energy with maximized parallelism. This forms a physics solver that can achieve numerical convergence with unconditional stability and exceptional computation performance. It can also fit in a given computation budget by simply limiting the iteration count while maintaining its stability and superior convergence rate. We present and evaluate our method in the context of elastic body dynamics, providing details of all essential components and showing that it outperforms alternative techniques. In addition, we discuss and show examples of how our method can be used for other simulation systems, including particle-based simulations and rigid bodies.

Funder

NSF

Publisher

Association for Computing Machinery (ACM)

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