SUBGRANT OF MCA02N013P/CAR TERASCALE SIMULATION TECHNIQUES FOR CHEMISTRY, MATER

MCA02N013P/CAR 化学、材料的万亿级模拟技术的子项目

• 批准号: 7601264
• 负责人: MICHAEL L. KLEIN
• 金额: $ 0.03万
• 依托单位: CARNEGIE-MELLON UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2007
• 资助国家: 美国
• 起止时间: 2007-08-01 至 2008-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7601264
• 关键词: Algorithms; Architecture; Area; Arts; Biology; Biomimetics; Catalysis; Chemistry; Collaborations; Communities; Complex; Computational Science; Computer Retrieval of Information on Scientific Projects Database; Computer software; Computers; Condition; Conscious; Devices; Education and Outreach; Electronics; Engineering; Event; Funding; Future; Goals; Grant; High Performance Computing; Industry; Information Technology; Institution; International; Internet; Knowledge; Lead; Light; Methodology; Modeling; Molecular; Performance; Planets; Polymers; Process; Property; Range; Research; Research Personnel; Resources; Sampling; Science; Scientist; Secondary to; Software Engineering; Source; Techniques; Technology; Time; United States National Institutes of Health; Use of New Techniques; base; catalyst; chemical bond; design; enzyme mechanism; improved; large scale simulation; molecular scale; nanoscale; nanoscience; next generation; novel; open source; programs; simulation; tool

This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. The subproject and investigator (PI) may have received primary funding from another NIH source, and thus could be represented in other CRISP entries. The institution listed is for the Center, which is not necessarily the institution for the investigator. Information Technology (IT) has transformed computational science to the extent that realistic, atom-based simulations of key processes in chemistry, geoscience, nanoscience science and engineering, and biology can now be tackled using Car-Parrinello ab initio molecular dynamics1 (CPAIMD, or more simply, CPMD) implemented on high performance computing (HPC) platforms. These calculations, which can model complex events such as chemical bond forming and breaking, have enormous potential to impact Science and Technology, e.g., through (1) the design of new industrial catalysts that generate novel polymers with improved properties; (2) the study of materials under extreme conditions found in Earth's mantle and cores of planets; (3) the analysis of nanoscale, and even molecular scale, devices, which could revolutionize the electronics and computer industries; and (4) examination of the mechanism of enzyme catalysis to enable the design of cheap, artificial catalysts (biomimetics) of high efficiency. Although CPMD is very powerful, it is too computationally intensive to be performed routinely on current computing platforms, which limit accessible time and spatial scales. The goal of this project is to design and build a framework to seamlessly enable new CPMD applications on future HPC platforms and thereby greatly expand the domain of utility of this critically important applications software. In light of CPMD's tremendous promise to advance science and technology, the exciting corresponding IT research challenges, and the educational opportunities these challenges embody, it is appropriate and timely to form a tightly knit, diverse Collaborative which combines application scientists (Car, Klein, Martyna, Tuckerman, Selloni) with both hardware (Torrellas) and software computer scientists (Kal, Nystrom) to aggressively advance the state of the art. The Collaborative will: (1) improve the methodology and sampling algorithms to permit larger scale simulations of higher accuracy; (2) employ next generation software engineering tools to design and implement parallel algorithms, which scale on thousands of processors in the near term and lead to scaling on much larger machines in the far term; (3) make available new, extensible object-oriented open source software modules for CPMD to the community via the Web with annual upgrades; (4) regularly carry out performance analyses, which will be used to fuel the design of novel hardware architectures; (5) use the new techniques and software to carry out applications projects in technologically important areas; (6) transfer the knowledge thus gained to the community through diversity- conscious outreach and education programs ranging from the secondary to graduate levels as well as through proven international academic and industrial collaborations.

这个子项目是许多利用 由NIH/NCRR资助的中心赠款提供的资源。子项目和 研究者（PI）可能从另一个NIH来源获得了主要资金， 因此可以在其他CRISP条目中表示。所列机构为 研究中心，而研究中心不一定是研究者所在的机构。 信息技术（IT）已经将计算科学转变为 范围内，现实的，基于原子的模拟关键过程， 化学、地球科学、纳米科学和工程以及生物学可以 现在使用Car-Parrinello从头分子动力学1（CPAIMD， 或者更简单地说，CPMD）在高性能计算（HPC）上实现， 平台 这些计算，可以模拟复杂的事件，如化学键 形成和打破，有巨大的潜力，影响科学和 技术，例如，通过（1）设计新的工业催化剂， 产生具有改进性能的新型聚合物;（2）研究 在地球地幔和地核中发现的极端条件下的物质 行星;（3）分析纳米尺度，甚至分子尺度，设备， 它可能会彻底改变电子和计算机行业;以及（4） 酶催化机制的研究，使设计 廉价、高效的人造催化剂（仿生学）。 虽然CPMD非常强大，但它的计算量太大， 在当前的计算平台上进行常规操作，这限制了可访问性 时间和空间尺度。该项目的目标是设计和建造一个 在未来HPC上无缝启用新CPMD应用程序的框架 平台，从而大大扩展了这一实用领域 重要的应用软件。鉴于CPMD的巨大 承诺推进科学技术，令人兴奋的相应IT 研究的挑战，以及这些挑战带来的教育机会 体现，是适当和及时地形成一个紧密结合，多样化， 合作，结合应用科学家（汽车，克莱因，Martyna， 塔克曼，Selloni），硬件（Torrellas）和软件计算机 科学家（Kal，Nystrom）积极推进最先进的技术。 合作将：（1）改进方法和抽样算法 允许更大规模的更高精度的模拟;（2）使用下一个 第二代软件工程工具来设计和实现并行 算法，在短期内可以在数千个处理器上扩展， 从长远来看，这将导致在更大的机器上扩展;（3）使可用 用于CPMD的新的、可扩展的面向对象的开源软件模块， 社区通过网络进行年度升级;（4）定期开展 性能分析，这将用于燃料的设计， （5）采用新的技术和软件实现 在重要技术领域的应用项目;（6）转让 通过多样性意识， 从中学到研究生的推广和教育计划 水平，以及通过证明国际学术和工业 合作。