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.

未来的petaflop模拟现实的生物和物理系统将必然涉及并发多尺度建模。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，这是同类模型中的第一个，由100个大型3D动脉（Macrovascular Network，MaN），1000万个小动脉（Mesovascular Network，MeN）和10亿个毛细血管（Microvascular Network，MiN）组成。的三个层次的MAN-MeN-MiN集成提供了一个通用的平台，用于开发混合确定性随机系统，可扩展的算法，可扩展的多尺度软件来处理异构偏微分方程之间的耦合，也连续和原子的配方。在他们对人体动脉树和新的大脑成像数据的初步工作的基础上，PI提出了基于图像的3D Navier-Stokes模拟来完全解析MaN，并结合MeN和MiN的亚像素随机模拟来完成闭合。 项目将实现MPI/UPC混合模型，以利用两种编程范式的优势：MPI中进程控制的高可扩展性和丰富功能，以及UPC中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，特别是用于动态细化。主要的软件进步将是针对多尺度应用（如MaN-MeN-MiN问题）在单个或多个petaflop平台上开发MPIg。更广泛的影响：这项工作将有助于计算数学（接口异构偏微分方程，也偏微分方程原子系统）;计算机科学（UPC/MPI的发展，多尺度MPIg，并增加供应商提供的MPI在MPIg的杠杆作用）;和生物工程（生物力学网关模拟大脑病理）。这个提议是变革性的，因为它将计算范式转移到一个新的水平（高于最先进水平的数量级），这将首次允许健康和疾病中的血管系统的逼真模拟。我们提出的peta°op计算的验证算法在许多多尺度生物和物理应用中具有普遍意义，包括所有生物体的血管树以及核反应堆和其他动力/化学工厂的模拟。以人脑为背景的新仿真环境，对于培训新一代跨学科科学家，使他们能够自如地使用多尺度数学和可扩展的软件工具进行极限计算至关重要。项目将吸引博士后，研究生，本科生和高中生。我们将使用3D沉浸式/交互式可视化作为机会，对学生进行模拟、可预测性以及计算机科学、工程和应用数学的其他问题的教育。外联活动将涉及初中和高中的女生以及教育和培训部特别高中的学生。