CAREER: Scalable Algorithms for Extreme Computing on Heterogeneous Hardware, with Applications in Fluids and Biology

目前，世界范围内都在寻求在本十年结束时实现艾级计算，特别是在美国以及中国和日本。在美国，总统的美国创新战略（2009年）明确列出了其目标之一，即通过一台艾级计算机大幅提高我们的模拟能力。实现这一目标的挑战是前所未有的：功率限制，微芯片制造达到物理极限，计算能力和互连带宽之间的日益不平衡，以及系统中内核数量的不断增加，其中最优先的事项是开发可扩展的算法，可以利用新系统的巨大并行性，并培养下一代计算科学家。其中第一个是在这个职业生涯项目的科学部分的中心。一种潜在的变革性组合正在出现，其中一类分层算法提供与问题大小成线性的理想缩放，以优异的性能映射到众核硬件（如GPU）。将进行数学上的改进，例如将树码和快速多极方法的要素结合起来，避免通信和同步，动态误差控制和计算的自动调整。该研究项目是跨学科的垂直整合，包括流体动力学和生物系统的极端规模应用。该项目将产生高度可扩展的科学软件，重新制定算法，以实现众核硬件的最大性能。通过开源模型进行传播和管理，所提供的计算基础设施将在重点应用领域之外产生最大的影响。能够扩展到数百万个处理器的社区软件对于利用后千万亿次系统至关重要，而该项目旨在提供这一点。另一方面，该计划的教育部分建立在PI在使用技术支持学习以及促进国际合作和推广方面的成功记录之上。该计划包括利用技术加强教育环境，用于课程教学和促进国家的科学素养（通过开放式课件）。培养下一代计算科学家的目标将通过校外高级培训活动和在线学习媒体来实现。

There is currently a world-wide quest to achieve exascale computing by the end of the decade, with vigorous efforts in the US as well as China and Japan, in particular. In the US, the President's Strategy for American Innovation (2009) explicitly lists among its goals to dramatically increase our simulations capacity via an exascale computer. The challenges to achieve this goal are unprecedented: power constraints, microchip fabrication reaching physical limits, the growing imbalance between compute capacity and interconnect bandwidth, and the ever increasing number of cores in a system.Among the matters of highest priority are development of scalable algorithms that can exploit the enormous parallelism of new systems, and educating the next generation of computational scientists. The first of these is at the center of the scientific part of this CAREER project. A potentially transformative combination is emerging where a class of hierarchical algorithms, offering ideal scaling linear with problem size, maps with excellent performance to many-core hardware (such as GPUs). Algorithmic improvements will be undertaken, such as combining elements of treecodes and fast multipole methods, communication and synchronization avoidance, dynamic error control and auto-tuning of the computation. The research program is vertically integrated across disciplines, including applications at extreme scales in fluid dynamics and biological systems.This project will produce highly scalable scientific software, reformulating the algorithms to achieve maximum performance in many-core hardware. Disseminated and curated via the open-source model, the computational infrastructure delivered will offer maximum impact, beyond the application areas of focus. Community software that is able to scale to millions of processors will be crucial to exploit post-petascale systems, and this project aims to provide that. The educational part of this program, on the other hand, builds on the PI's track record of success both in the use of technology to support learning, and in catalyzing international collaboration and outreach. The program includes enhancing educational environments using technology for both curricular instruction and contributing to the nation's science literacy (via open courseware). The goals of fostering the next generation of computational scientists will be pursued via extra-mural advanced training events, and online learning media.