Collaborative Research: Scalable Multiscale Models for the Cerebrovasculature: Algorithms, Software and Petaflop Simulations

合作研究：可扩展的脑血管多尺度模型：算法、软件和千万亿次模拟

• 批准号: 0904190
• 负责人: Michael Papka
• 金额: $ 27.65万
• 依托单位: University of Chicago
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2009
• 资助国家: 美国
• 起止时间: 2009-09-01 至 2013-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0904190&HistoricalAwards=false
• 关键词: Collaborative; Research; Scalable; Multiscale; Models

Future petaflop simulations of realistic biological and physical systems will necessarily involve concurrent multiscale modeling. This project will address fundamental mathematical, algorithmic and software issues for simulating a human brain vascular model, the first of its kind, consisting of 100 large 3D arteries (Macrovascular Network, MaN), 10 million arterioles (Mesovascular Network,MeN) and one billion capillaries (Microvascular Network, MiN). The three-level MaN-MeN-MiN integration offers a general platform for developing hybrid deterministic-stochastic systems, scalable algorithms, and scalable multiscale software to handle coupling between heterogeneous PDEs and also between continuum and atomistic formulations. Building upon their initial work on the human arterial tree and the new brain imaging data, PIs propose image-based 3D Navier-Stokes simulations for fully resolving MaN, coupled to subpixel stochastic simulations of MeN and MiN to complete the closure. Project will implement an MPI/UPC hybrid model to exploit the strengths of both programming paradigms: the high scalability and rich functionality for process control in MPI, and the low communication overhead for small messages and fine-grain parallelism in UPC. We will further seek to integrate multi-threading into the MPI/UPC model, especially for dynamic refinement. The main software advancement will be the development of MPIg tailored for multiscale applications, like the MaN-MeN-MiN problem, on a single or multiple petaflop platforms. Several open issues associated with co-processing and visualization of petabyte-size data will be also addressed. Broader Impact: This work will contribute to Computational Mathematics (interfacing heterogeneous PDEs, and also PDEs-atomistic systems); to Computer Science (development of UPC/MPI, multiscale MPIg, and increased leverage of vendor-supplied MPI in MPIg); and Bioengineering (biomechanics gateway to simulate brain pathologies). This proposal is transformative in that it shifts the computational paradigm to a new level (orders of magnitude above the state-of-the-art) that will allow, for first time, realistic simulations of cerebrovasculature in health and disease. The validated algorithms for peta°op computing we propose are of general interest for use in many multiscale biological and physical applications, including vascular trees of all living organisms and also in simulations of nuclear reactors and other power/chemical plants. The new simulation environment, with the human brain as a backdrop, will be critical in training a new generation of inter-disciplinary scientists to be comfortable in using multiscale mathematics and scalable software tools for extreme computing. Project will engage postdocs, graduate, undergraduate and high school students. We will use 3D immersive/interactive visualizations as an opportunity to educate students about simulation, predictability, and other issues of computer science, engineering, and applied mathematics. Outreach activities will involve female students from middle and high schools and students from the special MET high schools.

未来对现实生物和物理系统的Petaflop模拟将必然涉及并发的多尺度建模。这个项目将解决模拟人类脑血管模型的基本数学、算法和软件问题，这是第一个此类模型，由100个大型3D动脉(大血管网络，MAN)、1000万个小动脉(中血管网络，MEN)和10亿个毛细血管(微血管网络，MIN)组成。三级人-人-分集成为开发混合确定性-随机系统、可扩展的算法和可扩展的多尺度软件提供了通用平台，以处理不同类型的PDE之间的耦合以及连续和原子公式之间的耦合。基于他们在人类动脉树和新的脑成像数据上的初步工作，PI提出了基于图像的3D Navier-Stokes模拟来完全解析MAN，并结合亚像素随机模拟来完成MAN和MIN的闭合。Project将实现MPI/UPC混合模型，以利用这两种编程范例的优点：MPI的高可伸缩性和丰富的过程控制功能，以及UPC的小消息和细粒度并行的低通信开销。我们将进一步寻求将多线程集成到MPI/UPC模型中，特别是在动态优化方面。主要的软件进步将是为单个或多个Petaflop平台上的多尺度应用(如人-人-分钟问题)量身定做的MPIG的开发。还将讨论与PB级数据的协同处理和可视化相关的几个未决问题。更广泛的影响：这项工作将有助于计算数学(连接不同种类的PDE，以及PDE原子系统)；计算机科学(开发UPC/MPI、多尺度MPIG，并在MPIG中增加供应商提供的MPI的杠杆作用)；生物工程(模拟大脑病理的生物力学门户)。这一提议具有变革性，因为它将计算范式转移到一个新的水平(比最先进的水平高出几个数量级)，这将首次允许对健康和疾病中的脑血管系统进行逼真的模拟。我们提出的经过验证的Peta°op计算算法在许多多尺度生物和物理应用中具有普遍意义，包括所有生物的维管树以及核反应堆和其他发电厂/化工厂的模拟。以人脑为背景的新模拟环境将对培养新一代跨学科科学家熟练使用多尺度数学和可扩展软件工具进行极端计算至关重要。该项目将吸引博士后、研究生、本科生和高中生参与。我们将使用3D沉浸式/交互式可视化作为一个机会，教育学生关于模拟、可预测性和计算机科学、工程和应用数学的其他问题。外展活动将包括初中和高中的女学生以及特殊大都会中学的学生。