XPS:FULL:DSD: A novel framework for developing highly scalable and energy efficient guaranteed quality mesh generation for 3D and 4D finite element analysis

计算科学是“三大支柱”之一，与传统的科学和工程理论和物理实验研究相辅相成。并行有限元网格生成是这一支柱的关键组成部分，对于越来越多的工程和生命科学应用变得更加重要。这个项目将建立一个轨迹来交付第一个艾级级非结构有限元(FE)保证质量的Delaunay网格生成。为什么FE网格生成是一个重要的计算科学工具？许多用来模拟人体血液流动等复杂多尺度现象的偏微分方程(PDE)只能用数值逼近技术来求解。这些技术需要通过将区域细分为更简单的几何形状来近似区域，例如分别在二维和三维中的三角形和四面体。该项目的重点是用于生命科学应用的3D和4D细分方法，例如脑血管疾病(CVD，或中风)的血流模拟，脑血管疾病是美国主要的自然死亡原因之一。为了提供亿级级的网格生成，该项目将使用比当今最先进的方法少得多的电力来实现十亿路并发。这一目标将通过以下三个目标来实现：(1)将多种并行Delaunay网格生成方法集成到一个伸缩框架中。(2)开发描述该框架固有的并发性和数据访问模式的应用程序规范模型。(3)开发适用于大规模并行网格生成方法的域特定能效和组件级(核心和内存)功率缩放。该项目将在许多其他生命科学应用中产生更广泛的影响，例如与总统的大脑倡议相关的应用。例如，该项目的网格生成技术可以定制为(到2020年)执行计算机模拟，以了解人类大脑的电路-这是帮助了解帕金森氏症和阿尔茨海默氏症等疾病的重要里程碑，预计这些疾病将随着美国人口老龄化而增加。最后，这个项目将通过国际和平协会的功绩外展计划，为K-12和大学生的STEM教育做出贡献。PI的目标是“指导、激励和留住”学生，并帮助他们确定STEM学习领域，将他们转变为负责任的大学毕业生。PI的优点新生研讨会(与传统的新生研讨会不同)使学生在本科生研究体验(REU)活动的背景下(基于学生的兴趣)与非常明显的国家优先事项，如总统的大脑倡议，重新联系起来。功绩计划涵盖了各种主题，以尽可能多地接触到具有不同兴趣和背景的学生。我们的目标是培养计算科学家成为企业家，能够理解我们今天在医疗保健方面面临的伦理、经济和研究挑战。

Computational science is one of the "three pillars," complementing traditional theoretical and physical experimental studies in science and engineering. Parallel finite element mesh generation is a critical building block for this pillar and is becoming even more relevant for a growing number of engineering and life science applications. This project will set up a trajectory to deliver the first exascale-era unstructured finite element (FE) guaranteed quality Delaunay mesh generation.Why is FE mesh generation an important computational science tool? Many partial differential equations (PDEs) that are used to model complex multi-scale phenomena such as blood flow in the human body can only be solved by numerical approximation techniques. These techniques require the approximation of the domain by tessellating it into simpler geometric shapes such as triangles and tetrahedra in two and three dimensions, respectively. This project's focus is in 3D and 4D tessellation methods for life science applications such as blood flow simulations for Cerebro-Vascular Disease (CVD, or stroke), one of the leading natural causes of death in the US. In order to deliver exascale-era mesh generation, this project is set to achieve billion-way concurrency using substantially less electric power than today's state-of-the-art methods. This goal will be achieved by focusing on the following three objectives: (1) Integration of multiple parallel Delaunay mesh generation methods into a telescopic framework. (2) Development of application-specific models that describe the inherent concurrency and data access patterns of this framework. (3) Development of domain-specific energy-efficient and component-level (core and memory) power scaling for massively parallel mesh generation methods. This project will have broader impact in many other life science applications such as those related to the President's BRAIN Initiative. For example, the mesh generation techniques from this project can be customized to perform (by 2020) computer simulations to understand the circuitry of the human brain - an important milestone to help understand diseases like Parkinson's and Alzheimer's, which are expected to increase with the aging of the U.S. population. Finally, this project will contribute via the PI's MERIT outreach program for STEM education in K-12 and college students. The PI's goal is to "mentor, excite, and retain" students and help them to identify STEM areas of study that will transform them into responsible college graduates. The PI's MERIT Freshman Seminars (as opposed to traditional Freshman Seminars) re-connect students in the context of Research Experiences for Undergraduates (REU) activities (based on students interests) with highly visible national priorities such as the President's BRAIN Initiative. The MERIT program covers a variety of topics to reach as many students as possible with diverse interests and background. The goal is to prepare computational scientists to be entrepreneurs capable of understanding the ethical, economic, and research challenges in health care we face today.