We introduce Coordinate Condensation, a variant of coordinate descent that accelerates physics-based simulation by augmenting local coordinate updates with a Schur-complement-based subspace correction. Recent work by Lan et al. 2025 (JGS2) uses perturbation subspaces to augment local solves to account for global coupling, but their approach introduces damping that can degrade convergence. We reuse this subspace but solve for local and subspace displacements independently, eliminating this damping. For problems where the subspace adequately captures global coupling, our method achieves near-Newton convergence while retaining the efficiency and parallelism of coordinate descent. Through experiments across varying material stiffnesses and mesh resolutions, we show substantially faster convergence than both standard coordinate descent and JGS2. We also characterize when subspace-based coordinate methods succeed or fail, offering insights for future solver design.
翻译:本文提出坐标凝聚法,这是一种坐标下降法的变体,通过利用基于Schur补的子空间校正来增强局部坐标更新,从而加速基于物理的仿真。Lan等人2025年的近期工作(JGS2)使用扰动子空间来增强局部求解以考虑全局耦合,但其方法引入了可能降低收敛速度的阻尼。我们复用该子空间,但独立求解局部位移和子空间位移,从而消除了此阻尼。对于子空间能充分捕捉全局耦合的问题,我们的方法在保持坐标下降法效率和并行性的同时,实现了接近牛顿法的收敛速度。通过在不同材料刚度和网格分辨率下的实验,我们展示了该方法相比标准坐标下降法和JGS2均实现了显著更快的收敛。我们还分析了基于子空间的坐标方法何时成功或失败,为未来求解器设计提供了见解。