abstract
Model reduction has popularized itself for simulating elastic deformation
for graphics applications. While these techniques enjoy orders-of-magnitude
speedups at runtime simulation, the efficiency of precomputing reduced
subspaces remains largely overlooked. We present a complete system of
precomputation pipeline as a faster alternative to the classic linear and
nonlinear modal analysis. We identify three bottlenecks in the traditional
model reduction precomputation, namely modal matrix construction, cubature
training, and training dataset generation, and accelerate each of them.
Even with complex deformable models, our method has achieved orders-of-magnitude
speedups over the traditional precomputation steps, while retaining comparable
runtime simulation quality.
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bibtex citation
@article{Yang:2015:fastprecomp, title={Expediting Precomputation for Reduced Deformable Simulation}, author={Yang, Yin and Li, Dingzeyu and Xu, Weiwei and Tian, Yuan and Zheng, Changxi}, journal={ACM Trans. Graph.}, volume={34}, number={6}, year={2015}, doi={10.1145/2816795.2818089} }
acknowledgements
We thank anonymous reviewers for their feedback. This research was supported in part by the National Science Foundation (CRII-1464306, CAREER-1453101), National Science Foundation China (No. 61272392, No. 61322204), UNM RAC & OVPR research grants, and generous gifts from Intel and DJI. Any opinions, findings and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of funding agencies or others.