YASPS: A Symbolic Framework for Extensible, High-Performance IPC Simulation
Xuan Tang, Kemeng Huang, Gilbert Bernstein, Minchen Li, Tzumao Li
摘要
Incremental Potential Contact (IPC) has emerged as a robust and unifying formulation for contact-rich physical simulation by casting elasticity and collision handling as a single energy minimization problem. Achieving high performance, however, typically requires heavily specialized implementations that hard-code assumptions about energies, primitive types, and parameterizations, creating a major barrier to extensibility. Adding new energies or alternative parameterizations often requires re-deriving first and second-order derivatives, and implementing new assembly logic for the global Hessian and gradient. This challenge is further exacerbated by collision energies, where the same energy definition is often applied to mixed parameterizations, which can lead to a combinatorial explosion of parameterization-specific derivative and assembly cases. In this paper we introduce YASPS, a framework for physical simulation that resolves this limitation by making structural relationships explicit in a differentiable representation. YASPS introduces two relational operators, JOIN and UNION, which encode connectivity and heterogeneous parameterizations directly in the symbolic computation graph. Using symbolic differentiation over these operators, YASPS automatically derives local derivatives, and determines the induced sparsity and block structure of global gradients and Hessians from the same description while avoiding any code explosion induced by mixed-parameterizations. Targeting IPC workloads, YASPS compiles the resulting symbolic graphs into GPU kernels for local energy evaluation, derivative computation, and block-sparse matrix assembly, and solves the resulting Newton systems using a GPU-based iterative solver. This approach achieves performance competitive with state-of-the-art IPC implementations while enabling new energies and parameterizations to be added through localized symbolic definitions, without hand-written derivative or assembly code.
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它引用的顶会 Paper9
- DiffTaichi: Differentiable Programming for Physical SimulationYuanming Hu, Luke Anderson, Tzu-Mao Li, Qi Sun 等ICLR 2020 · 被引用 479 次
- Incremental potential contact: intersection-and inversion-free, large-deformation dynamicsMinchen Li, Zachary Ferguson, Teseo Schneider, Timothy R. Langlois 等SIGGRAPH 2020 · 被引用 320 次
- Codimensional incremental potential contactMinchen Li, Danny M. Kaufman, Chenfanfu JiangSIGGRAPH 2021 · 被引用 117 次
- Intersection-free rigid body dynamicsZachary Ferguson, Minchen Li, Teseo Schneider, Francisca Gil Ureta 等SIGGRAPH 2021 · 被引用 83 次
- Affine body dynamics: fast, stable and intersection-free simulation of stiff materialsLei Lan, Danny M. Kaufman, Minchen Li, Chenfanfu Jiang 等SIGGRAPH 2022 · 被引用 46 次
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