CHS: Small: Towards Next-Generation Large-Scale Nonlinear Deformable Simulation

CHS：小型：迈向下一代大规模非线性变形模拟

• 批准号: 2016414
• 负责人: Yin Yang
• 金额: $ 35.73万
• 依托单位: Clemson University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-11-15 至 2022-10-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2016414&HistoricalAwards=false
• 关键词: CHS; Small; Towards; Next; Generation

Using a digital computer to accurately simulate soft objects that deform under external interactions is a fundamental problem in a wide range of scientific and engineering fields. For example, without being able to deliver a faithful force-displacement response, virtual surgical training is hardly effective and provides users with misleading experiences. In the past decade, the number of simulation degrees of freedom (DOFs) for deformable models has increased from hundreds to hundreds-of-thousands and even millions. Computing hardware that has become more and more powerful has contributed significantly to this development, but unfortunately it is unlikely that in the future computer simulation will continue to benefit dramatically from increased processor frequency. Indeed, in the last few years the chip industry has already moved the emphasis from a faster processor clock to multi-core architectures. On the other hand, with the widespread adoption of advanced acquisition devices/techniques, the complexity and scale of the data that can be handled by computers have grown exponentially, and large-scale geometries are becoming ubiquitous in modern 3D data processing. This new era of data explosion imposes unprecedented challenges on deformable simulation. Existing methods typically use one-stop solvers that calculate all the unknown DOFs of a system, but that is computationally intensive due to the underlying high-dimensional numerical integration. Even with state-of-the-art hardware, deformable simulation can still take hours, days, or even weeks for massive scenarios. Clearly, conventional simulation methodologies fail to well accommodate distributed computing resource allocation, and become more and more cumbersome with bigger and bigger datasets. This calls for rebranded algorithmic frameworks and dedicated numerical procedures for large-scale geometrically-complex and nonlinear deformable models that empower next-generation graphics applications. Motivated by these grand challenges, this project systematically investigates a collection of theoretical advancements, computational techniques, and numerical implementations that push the frontier of large-scale nonlinear deformable models to "post Moore's law." Specifically, the intellectual merit of the research will comprise the following aspects:o The project will devise a theoretically grounded domain decomposition based parallel deformable simulator. By weakening inter-domain linkages, the domain-level computations become independent and parallelizable. The coupling mechanism will be generalized and enriched so that non-conforming and overlapping domain decompositions are made possible. This includes an in-depth optimization of the domain tessellation under specified hardware configurations. Simulation reusability will be further enhanced through a novel technique called cellular domains.o The project will deepen the current understanding of large-scale model reduction and re-forge this useful tool in the context of parallel computing. In particular, how to utilize power iteration to obtain the spectral analysis will be explored. Furthermore, geometry-based reduction directly dictates reduced DOFs and has a more robust simulation even under imposed extreme constraints.o A well-argued computational theory is less practicable unless encapsulated by a set of carefully engineered implementations. Accordingly, the project will also design customized numerical procedures paired with proposed algorithmic techniques, and the entire simulation framework will be fine-tuned at the system level, solver level, and sub-solver level by leveraging unique data patterns, numerical behaviors, and problem structures of domain decomposed deformable models.o As a testbed platform, the project will develop a novel real-time human tongue motion visualization system. Over 8% of U.S. children have a communication or swallowing disorder. Built upon the new deformation solver, an ultrasound-imaging-driven real-time human tongue visualization system will be developed to assist doctors and speech therapists to better understand the pathological mechanism behind this disease and plan more effective subject-specific medical/physical treatments.

使用数字计算机精确模拟在外部相互作用下变形的软物体是广泛科学和工程领域的一个基本问题。 例如，如果无法提供忠实的力位移响应，虚拟手术训练就很难有效，并且会给用户带来误导性的体验。 在过去的十年中，可变形模型的模拟自由度（DOF）数量已从数百个增加到数十万甚至数百万。 变得越来越强大的计算硬件对这一发展做出了重大贡献，但不幸的是，未来计算机模拟不太可能继续从处理器频率的增加中显着受益。 事实上，在过去几年中，芯片行业已经将重点从更快的处理器时钟转移到多核架构。 另一方面，随着先进采集设备/技术的广泛采用，计算机可处理的数据的复杂性和规模呈指数级增长，大型几何图形在现代 3D 数据处理中变得无处不在。 数据爆炸的新时代给变形模拟带来了前所未有的挑战。 现有方法通常使用一站式求解器来计算系统的所有未知自由度，但由于底层的高维数值积分，计算量很大。 即使使用最先进的硬件，对于大规模场景来说，变形模拟仍然需要数小时、数天甚至数周的时间。 显然，传统的模拟方法无法很好地适应分布式计算资源分配，并且随着数据集越来越大而变得越来越繁琐。 这需要针对大规模复杂几何和非线性变形模型重新命名的算法框架和专用数值程序，以支持下一代图形应用程序。 在这些重大挑战的推动下，该项目系统地研究了一系列理论进步、计算技术和数值实现，将大规模非线性变形模型的前沿推向了“后摩尔定律”。 具体来说，该研究的智力价值将包括以下几个方面： o 该项目将设计一种基于理论基础的域分解的并行可变形模拟器。 通过削弱域间联系，域级计算变得独立且可并行。 耦合机制将得到推广和丰富，从而使非一致性和重叠域分解成为可能。 这包括在指定硬件配置下对域细分进行深入优化。 模拟的可重用性将通过一种称为细胞域的新技术得到进一步增强。该项目将加深当前对大规模模型简化的理解，并在并行计算的背景下重新打造这一有用的工具。 特别是，将探讨如何利用幂迭代来获得谱分析。 此外，基于几何的简化直接决定了减少的自由度，并且即使在施加的极端约束下也具有更稳健的模拟。除非通过一组精心设计的实现来封装，否则经过充分论证的计算理论不太实用。 因此，该项目还将设计与所提出的算法技术相结合的定制数值程序，并且通过利用独特的数据模式、数值行为和问题，整个仿真框架将在系统级、求解器级和子求解器级进行微调域分解变形模型的结构。作为测试平台，该项目将开发一种新颖的实时人类舌头运动可视化系统。 超过 8% 的美国儿童患有沟通或吞咽障碍。 基于新的变形解算器，将开发超声波成像驱动的实时人类舌头可视化系统，以帮助医生和言语治疗师更好地了解这种疾病背后的病理机制，并计划更有效的针对特定主题的医疗/物理治疗。

项目成果

Medial Elastics: Efficient and Collision-Ready Deformation via Medial Axis Transform

内侧弹性：通过内侧轴变换实现高效且防碰撞的变形

• DOI: 10.1145/3384515
• 发表时间: 2020-06
• 期刊: ACM Transactions on Graphics
• 影响因子: 6.2
• 作者: Lan, Lei;Luo, Ran;Fratarcangeli, Marco;Xu, Weiwei;Wang, Huamin;Guo, Xiaohu;Yao, Junfeng;Yang, Yin
• 通讯作者: Yang, Yin

Parallel iterative solvers for real-time elastic deformations

用于实时弹性变形的并行迭代求解器

• DOI: 10.1145/3277644.3277779
• 发表时间: 2018-12-04
• 期刊: SIGGRAPH Asia 2018 Courses
• 作者: M. Fratarcangeli;Huamin Wang;Yin Yang
• 通讯作者: Yin Yang

Computational Design of Skinned Quad-Robots

蒙皮四机器人的计算设计

• DOI: 10.1109/tvcg.2019.2957218
• 发表时间: 2019-07-01
• 期刊: IEEE Transactions on Visualization and Computer Graphics
• 影响因子: 5.2
• 作者: Xudong Feng;Jiafeng Liu;Huamin Wang;Yin Yang;H. Bao;B. Bickel;Weiwei Xu
• 通讯作者: Weiwei Xu