GAMES Webinar 2023 – 269期(Simulating Meshes) | 余畅(电子科技大学),张嘉懿(斯坦福大学)

【GAMES Webinar 2023-269期】(模拟专题-Simulating Meshes)



报告题目:MeshTaichi: A Compiler for Efficient Mesh-based Operations


Meshes are an indispensable representation in many graphics applications because they provide conformal spatial discretization. However, mesh-based operations are often slow due to unstructured memory access patterns. We propose MeshTaichi, a novel mesh compiler that provides an intuitive programming model for efficient mesh-based operations. Our programming model hides the complex indexing system from users and allows users to write mesh-based operations using reference-style neighborhood queries. Our compiler achieves its high performance by exploiting data locality. We partition input meshes and prepare the wanted relations by inspecting users’ code during compile time. During run time, we further utilize on-chip memory (shared memory on GPU and L1 cache on CPU) to access the wanted attributes of mesh elements efficiently. Our compiler decouples low-level optimization options with computations, so that users can explore different localized data attributes and different memory orderings without changing their computation code. As a result, users can write concise code using our programming model to generate efficient mesh-based computations on both CPU and GPU backends. We test MeshTaichi on a variety of physically-based simulation and geometry processing applications with both triangle and tetrahedron meshes. MeshTaichi achieves a consistent speedup ranging from 1.4 times to 6 times, compared to state-of-the-art mesh data structures and compilers.


Chang Yu is a fourth-year undergraduate in Software Engineering at the University of Electronic Science and Technology of China (UESTC), and a research & development intern at Taichi Graphics, advised by Dr. Tiantian Liu. His research interests lie in computer graphics and computational physics. In particular, He devotes himself to physically-based simulation and high-performance computing on modern graphics architecture.


报告嘉宾:张嘉懿(斯坦福大学 )


报告题目:Progressive Simulation for Cloth Quasistatics


The trade-off between speed and fidelity in cloth simulation is a fundamental computational problem in computer graphics and computational design. Coarse cloth models provide the interactive performance required by de- signers, but they can not be simulated at higher resolutions (“up-resed”) without introducing simulation artifacts and/or unpredicted outcomes, such as different folds, wrinkles and drapes. But how can a coarse simulation predict the result of an unconstrained, high-resolution simulation that has not yet been run?
We propose Progressive Cloth Simulation (PCS), a new forward simulation method for efficient preview of cloth quasistatics on exceedingly coarse triangle meshes with consistent and progressive improvement over a hierarchy of increasingly higher-resolution models. PCS provides an efficient coarse previewing simulation method that predicts the coarse-scale folds and wrinkles that will be generated by a corresponding converged, high-fidelity C-IPC simulation of the cloth drape’s equilibrium. For each preview PCS can generate an increasing-resolution sequence of consistent models that progress towards this converged solution. This successive improvement can then be interrupted at any point, for example, whenever design parameters are updated. PCS then ensures feasibility at all resolutions, so that predicted solutions remain intersection-free and capture the complex folding and buckling behaviors of frictionally contacting cloth.


Jiayi (Eris) Zhang is a second-year Ph.D. student in in Computer Science at Stanford University, advised by Prof. Doug L. James. Her research has been generously supported by a Stanford Graduate Fellowship. Previously, she completed her undergraduate degree in Computer Science and Mathematics at the University of Toronto, advised by Prof. Alec Jacobson. Her current research has been primarily focusing on developing computational models and tools via numerical methods for enhancing user creativity and productivity in design, animation and simulation.





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