MRI: Acquisition of a Next Generation, Data-Centric Supercomputer

MRI：获取下一代以数据为中心的超级计算机

• 批准号: 1828083
• 负责人: Christopher Carothers
• 金额: $ 99.9万
• 依托单位: Rensselaer Polytechnic Institute
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2018
• 资助国家: 美国
• 起止时间: 2018-09-01 至 2021-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1828083&HistoricalAwards=false
• 关键词: MRI; Acquisition; Next; Generation; Data

The project will support the acquisition of a data centric supercomputer at Rensselaer Polytechnic Institute (RPI). This instrument will lead to significant advancements in science and engineering problems currently being tackled at RPI's Center for Computational Innovations (CCI) for applications including: the definition of new designed materials, applying active flows control for energy savings and microbiological systems modeling for medical treatment planning. The research will also include the development of new extreme-scale simulation technologies, graph analysis algorithms and the construction of entirely new simulation workflows. Hundreds of researchers and students from over 20 universities, 5 DOE national laboratories, 3 major industrial research centers (Corning, GE and IBM), 50 faculty, 4 start-ups across 11 U.S. states will take advantage of this proposed cyberinstrument to continue making a deep impact on their research. Student participation has been key to CCI's current success and national interest is anticipated not only due to the instrument's ability to advance current research but also due to its potential as a prototype model for future exascale systems. Students engaged in projects supported by the instrument will become the next generation of compute and data intensive experts.The new instrument integrates IBM POWER9 CPUs with next generation NVIDIA Volta GPUs into a hardware accelerated unified memory system (e.g., cache coherent). Additionally, all compute nodes are augmented with non-volatile memory storage, and a subset of the nodes include FPGA acceleration. The system will be used by faculty, students and CCI collaborators to address current barriers caused by the need to interact with massive data volumes that are used in and produced by next generation simulation tools. The cyberinstrument and algorithmic developments to be carried out will enable a new level of understanding and enhance our ability to solve many key challenges including: the accurate diagnosis of breast cancer directly from large-scale image datasets; semantic integration of the abundance of heterogeneous, multimodal, and multiscale data to improve personal health; modeling plasmas in fusion reactors; modeling active flow control devices that will greatly increase the weather conditions under which wind turbines will produce electricity; and combined biological data and model integration on molecular, cellular, and organ levels to understand organism-level phenomena and gain predictive understanding in systems biology.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

该项目将支持Rensselaer Polytechnic Institute（RPI）收购一台以数据为中心的超级计算机。该仪器将导致RPI计算创新中心（CCI）目前正在解决的科学和工程问题的重大进展，其应用包括：新设计材料的定义，应用主动流量控制以节省能源和微生物系统建模用于医疗计划。该研究还将包括开发新的极端规模仿真技术，图形分析算法和构建全新的仿真工作流程。来自美国11个州的20多所大学、5个能源部国家实验室、3个主要工业研究中心（康宁、通用电气和IBM）、50名教师和4家初创企业的数百名研究人员和学生将利用这一拟议中的网络工具继续对他们的研究产生深远的影响。学生的参与是CCI目前成功的关键，预计国家的兴趣不仅是由于该仪器能够推进当前的研究，而且还由于其作为未来艾级系统原型模型的潜力。 参与该仪器支持的项目的学生将成为下一代计算和数据密集型专家。新仪器将IBM POWER 9 CPU与下一代NVIDIA Volta GPU集成到硬件加速的统一内存系统中（例如，高速缓存相干）。此外，所有计算节点都增加了非易失性存储器存储，并且节点的子集包括FPGA加速。该系统将由教师，学生和CCI合作者使用，以解决当前由于需要与下一代仿真工具中使用和产生的大量数据进行交互而造成的障碍。将要进行的网络仪器和算法开发将使我们的理解达到一个新的水平，并提高我们解决许多关键挑战的能力，包括：直接从大规模图像数据集准确诊断乳腺癌;丰富的异质性，多模态和多尺度数据的语义整合，以改善个人健康;在聚变反应堆中模拟等离子体;对将大大增加风力涡轮机将产生电力的天气条件的主动流控制装置进行建模;结合生物学数据和模型集成在分子，细胞，和器官水平来理解有机体-该奖项反映了NSF的法定使命，并已被认为是值得通过评估使用的支持基金会的学术价值和更广泛的影响审查标准。