Presents a consensus-based ADMM distributed version of Affine Body Dynamics that enables scalable multi-node simulation while preserving IPC robustness and non-penetration.
ACM Transactions on Graphics (TOG) , volume=
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cs.GR 4years
2026 4verdicts
UNVERDICTED 4representative citing papers
AGIPC achieves up to 3x speedup in GPU IPC by performing adaptive algebraic coarsening inside the solver while keeping results visually indistinguishable from the fine-scale version.
MAS-PNCG accelerates IPC by incrementally updating multilevel MAS preconditioners via Sparse-Input Woodbury, adding Hessian-aware 2D subspace minimization and per-subdomain CCD, achieving up to 5.66x speedup over Newton-PCG baselines.
YASPS is a symbolic differentiable framework that uses JOIN and UNION operators to enable extensible high-performance IPC simulation on GPUs with automatic sparsity derivation and JIT kernel compilation.
citing papers explorer
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Distributed Affine Body Dynamics with Adaptive Consensus
Presents a consensus-based ADMM distributed version of Affine Body Dynamics that enables scalable multi-node simulation while preserving IPC robustness and non-penetration.
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AGIPC: Adaptive In-Solve Algebraic Coarsening for GPU IPC
AGIPC achieves up to 3x speedup in GPU IPC by performing adaptive algebraic coarsening inside the solver while keeping results visually indistinguishable from the fine-scale version.
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An Efficient Multilevel Preconditioned Nonlinear Conjugate Gradient Method for Incremental Potential Contact
MAS-PNCG accelerates IPC by incrementally updating multilevel MAS preconditioners via Sparse-Input Woodbury, adding Hessian-aware 2D subspace minimization and per-subdomain CCD, achieving up to 5.66x speedup over Newton-PCG baselines.
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YASPS: A Symbolic Framework for Extensible, High-Performance IPC Simulation
YASPS is a symbolic differentiable framework that uses JOIN and UNION operators to enable extensible high-performance IPC simulation on GPUs with automatic sparsity derivation and JIT kernel compilation.