# P-Cloth: Interactive Complex Cloth Simulation on Multi-GPU Systems using Dynamic Matrix Assembly and Pipelined Implicit Integrators

arXiv: https://arxiv.org/abs/2008.00409 · HTML: https://mlsanity.com/paper/2008.00409/

## Key facts

- Cited by 26 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 2 Aug 2020.

## Built on by (most cited first, 26 of 26)

- [DiffCloth: Differentiable Cloth Simulation with Dry Frictional Contact](https://mlsanity.com/paper/2106.05306/) (2021)
- [Predicting Loose-Fitting Garment Deformations Using Bone-Driven Motion Networks](https://mlsanity.com/paper/2205.01355/) (2022)
- [Text-to-Vector Generation with Neural Path Representation](https://mlsanity.com/paper/2405.10317/) (2024)
- [Learning to Generate 3D Shapes from a Single Example](https://mlsanity.com/paper/2208.02946/) (2022)
- [Dynamic Neural Garments](https://mlsanity.com/paper/2102.11811/) (2021)
- [PERGAMO: Personalized 3D Garments from Monocular Video](https://mlsanity.com/paper/2210.15040/) (2022)
- [Motion Guided Deep Dynamic 3D Garments](https://mlsanity.com/paper/2209.11449/) (2022)
- [AniClipart: Clipart Animation with Text-to-Video Priors](https://mlsanity.com/paper/2404.12347/) (2024)
- [SVGenius: Benchmarking LLMs in SVG Understanding, Editing and Generation](https://mlsanity.com/paper/2506.03139/) (2025)
- [N-Cloth: Predicting 3D Cloth Deformation with Mesh-Based Networks](https://mlsanity.com/paper/2112.06397/) (2021)
- [SVGen: Interpretable Vector Graphics Generation with Large Language Models](https://mlsanity.com/paper/2508.09168/) (2025)
- [SimpModeling: Sketching Implicit Field to Guide Mesh Modeling for 3D Animalmorphic Head Design](https://mlsanity.com/paper/2108.02548/) (2021)
- [Multi-Object Sketch Animation with Grouping and Motion Trajectory Priors](https://mlsanity.com/paper/2508.15535/) (2025)
- [Learning Anchor Transformations for 3D Garment Animation](https://mlsanity.com/paper/2304.00761/) (2023)
- [Text-Guided Vector Graphics Customization](https://mlsanity.com/paper/2309.12302/) (2023)
- [Image Vectorization with Depth: convexified shape layers with depth ordering](https://mlsanity.com/paper/2409.06648/) (2024)
- [Interactive Sketching of Mannequin Poses](https://mlsanity.com/paper/2212.07098/) (2022)
- [CTSN: Predicting Cloth Deformation for Skeleton-based Characters with a Two-stream Skinning Network](https://mlsanity.com/paper/2305.18808/) (2023)
- [Sketch2Arti: Sketch-based Articulation Modeling of CAD Objects](https://mlsanity.com/paper/2604.25781/) (2026)
- [PatternGSL: A Structured Specification Language for Template-Free and Simulation-Ready 3D Garments](https://mlsanity.com/paper/2606.24564/) (2026)
- [Garment Animation NeRF with Color Editing](https://mlsanity.com/paper/2407.19774/) (2024)
- [A Formalization of Image Vectorization by Region Merging](https://mlsanity.com/paper/2409.15940/) (2024)
- [Bringing Diversity from Diffusion Models to Semantic-Guided Face Asset Generation](https://mlsanity.com/paper/2504.15259/) (2025)
- [SketchAnimator: Animate Sketch via Motion Customization of Text-to-Video Diffusion Models](https://mlsanity.com/paper/2508.07149/) (2025)
- [One-shot Embroidery Customization via Contrastive LoRA Modulation](https://mlsanity.com/paper/2509.18948/) (2025)
- [Data-Efficient Brushstroke Generation with Diffusion Models for Oil Painting](https://mlsanity.com/paper/2603.01103/) (2026)

## Abstract (arXiv)

We present a novel parallel algorithm for cloth simulation that exploits multiple GPUs for fast computation and the handling of very high resolution meshes. To accelerate implicit integration, we describe new parallel algorithms for sparse matrix-vector multiplication (SpMV) and for dynamic matrix assembly on a multi-GPU workstation. Our algorithms use a novel work queue generation scheme for a fat-tree GPU interconnect topology. Furthermore, we present a novel collision handling scheme that uses spatial hashing for discrete and continuous collision detection along with a non-linear impact zone solver. Our parallel schemes can distribute the computation and storage overhead among multiple GPUs and enable us to perform almost interactive simulation on complex cloth meshes, which can hardly be handled on a single GPU due to memory limitations. We have evaluated the performance with two multi-GPU workstations (with 4 and 8 GPUs, respectively) on cloth meshes with 0.5-1.65M triangles. Our approach can reliably handle the collisions and generate vivid wrinkles and folds at 2-5 fps, which is significantly faster than prior cloth simulation systems. We observe almost linear speedups with respect to the number of GPUs.