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: 0904288
• 负责人: George Karniadakis
• 金额: $ 67.82万
• 依托单位: Brown University
• 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=0904288&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.

对现实生物系统和物理系统的未来PETAFLOP模拟必然涉及并发的多尺度建模。该项目将解决模拟人脑血管模型的基本数学，算法和软件问题，其中首先由100个大型3D动脉（大型3D动脉）（Macrascular Network，MAN），1000万个动脉（中气管网络，男性）和1000万个动脉和1000万个毛细管（Microsasculen Networkies）（微血管网络，最小）。三层人行为的集成提供了一个通用平台，可用于开发混合确定性系统，可扩展算法和可扩展的多尺度软件，以处理异质PDE之间以及持续和原子公式之间的耦合。基于他们在人类动脉树上的最初工作和新的脑成像数据的基础上，PIS提案基于图像的3D Navier-Stokess模拟了完全解决的人，并结合了男性和最小的子像素随机模拟，以完成封闭。项目将实施MPI/UPC混合模型，以利用两种编程范式的优势：MPI中过程控制的高扩展性和丰富功能，以及在UPC中用于小消息和细粒度并行性的低通信开销。我们将进一步寻求将多线程集成到MPI/UPC模型中，尤其是用于动态改进。主要的软件进步将是在单个或多个PETAFLOP平台上量身定制的用于多尺度应用程序的MPIG。与PBABYTES大小数据的共处理和可视化相关的几个开放问题也将得到解决。Boader的影响：这项工作将有助于计算数学（与异质PDES，以及PDES-Atomistic Systems相互交流）；进入计算机科学（开发UPC/MPI，多尺度MPIG以及MPIG中供应商供应商MPI的杠杆作用）；和生物工程（生物力学的网关，用于模拟脑病理学）。该提议具有变革性的是，它将计算范式转移到了一个新的水平（高于最先进的水平），这将首次允许对健康和疾病中的大脑脑堵嘴进行现实的模拟。我们建议的PETA°°OP计算算法是用于许多多尺度生物学和物理应用，包括所有生物体的血管树以及核反应堆和其他化学工厂的模拟。新的模拟环境以人脑为背景，对于培训新一代的跨学科科学家将很舒适，可以使用多尺度数学和可扩展的软件工具来进行极端计算。项目将与博士后，毕业生，本科和高中生联系。我们将使用3D沉浸式/交互式可视化作为机会，以教育学生有关计算机科学，工程和应用数学问题的模拟，可预测性以及其他问题。外展活动将涉及来自中学的女学生以及来自特殊的大都会高中的学生。