A GPU-based Streaming Algorithm for High-Resolution Cloth Simulation

simulation results generated using varying resolutions of the cloth mesh on the Buddha model: 20K, 500K, and 2M triangles (from left to right). Our new GPU-based streaming algorithm takes 138 seconds/frame to perform the entire simulation (including time integration, collision detection, and response) on a NVIDIA Tesla K20c GPU. It is about 126X faster than a single-threaded CPU-based algorithm. We present a GPU-based streaming algorithm to perform high-resolution and accurate cloth simulation. We map all the components of cloth simulation pipeline, including time integration, collision detection, collision response, and velocity updating to GPU-based kernels and data structures. Our algorithm perform intra-object and inter-object collisions, handles contacts and friction, and is able to accurately simulate folds and wrinkles. We describe the streaming pipeline and address many issues in terms of obtaining high throughput on many-core GPUs. In practice, our algorithm can perform high-fidelity simulation on a cloth mesh with 2M triangles using 3GB of GPU memory. We highlight the parallel performance of our algorithm on three different generations of GPUs. On a high-end NVIDIA Tesla K20c, we observe up to two orders of magnitude performance improvement as compared to a single-threaded CPU-based algorithm, and about one order of magnitude improvement over a 16-core CPU-based parallel implementation. c © 2013 The Author(s