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Research Infrastructure: MRI: Acquisition of a Big Data HPC Cluster for Interdisciplinary Research and Training

研究基础设施：MRI：收购大数据 HPC 集群以进行跨学科研究和培训

基本信息

批准号：
2215705
负责人：
Thomas Girke
金额：
$ 66万
依托单位：
University of California-Riverside
依托单位国家：
美国
项目类别：
Standard Grant
财政年份：
2022
资助国家：
美国
起止时间：
2022-09-01 至 2025-08-31
项目状态：
未结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=2215705&HistoricalAwards=false
关键词：
Research Infrastructure MRI Acquisition Big

项目摘要

An award is made to the University of California, Riverside (UCR) to acquire a Big Data High-Performance Computing (BD-HPC) cluster designed to enable novel and transformative research, outreach and training activities that are highly relevant to the environment and society. The system will be managed by UCR's HPC Center (HPCC) that serves a broad and diverse user population distributed across colleges and departments. As a highly shared resource, the instrument will enable a large number of NSF-funded programs, including those aiming to improve practices in agriculture, environmental protection, technology development and industry. Extensive educational and training activities are integrated to disseminate multidisciplinary concepts of Big Data Science. These outreach components will educate the public about the impact of Big Data Science on the environment, economy and society. The HPCC supports many undergraduate and graduate classes in a wide range of disciplines. Its resources are also instrumental for the development of new courses and programs in various data science areas. A high percentage of students in these classes and programs are from populations that are traditionally underrepresented in STEM disciplines. The availability of adequate computing and its beneficial impact on educational programs will attract outstanding students to computational and quantitative undergraduate and graduate programs. Combined with UCR’s diverse ethnicity and research mission, this investment will benefit a wide array of translational research directions and technology-based economic development initiatives.The new BD-HPC cluster will enable novel research that cannot be performed on UCR’s current research computing infrastructure or community cyberinfrastructure (CI), while also offering sufficient capacity to ensure support of ongoing research with greatly improved performance. Both current and new research addresses fundamental problems in a highly interdisciplinary environment bridging a broad array of science and engineering disciplines in basic and translational research. Grand challenge questions asked include: How do genetic and population dynamics determine phenotypic and evolutionary diversity? How can large-scale precision data be translated into improved stress and pathogen tolerance to feed a growing world population, and to develop interventions for reducing the rate and impact of environmental changes, natural disasters and climate change? How can quantitative modeling lead to high-performance molecules, materials, and help prevent wildfires and predict earthquakes? UCR researchers working on these problems are from a wide range of research specializations, including environmental science, agriculture, biology, chemistry, physics, engineering, computer science, statistics and applied mathematics. Since their research relies heavily on high-throughput and computational modeling approaches, the BD-HPC cluster will permit new computational approaches for solving these research problems.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.

加州大学河滨分校(UCR)被授予收购大数据高性能计算(BD-HPC)集群的奖项，该集群旨在支持与环境和社会高度相关的新颖和变革性研究、外联和培训活动。该系统将由UCR的HPC中心(HPCC)管理，该中心为分布在各学院和院系的广泛而多样化的用户群体提供服务。作为一种高度共享的资源，该工具将使NSF资助的大量项目成为可能，包括那些旨在改善农业、环境保护、技术开发和工业实践的项目。整合广泛的教育和培训活动，传播大数据科学的多学科概念。这些外展内容将教育公众了解大数据科学对环境、经济和社会的影响。HPCC支持许多不同学科的本科生和研究生班级。它的资源也有助于在各个数据科学领域开发新的课程和方案。在这些班级和项目中，很高比例的学生来自传统上在STEM学科中代表性不足的人群。充分计算的可用性及其对教育项目的有益影响将吸引优秀学生进入计算和量化本科和研究生课程。与UCR不同的种族和研究使命相结合，这项投资将使一系列翻译研究方向和基于技术的经济发展倡议受益。新的BD-HPC集群将使无法在UCR现有的研究计算基础设施或社区网络基础设施(CI)上执行的新颖研究成为可能，同时还提供足够的能力，以确保以极大提高的性能支持正在进行的研究。目前的研究和新的研究都是在一个高度跨学科的环境中解决基本问题，在基础研究和翻译研究中连接了广泛的科学和工程学科。提出的重大挑战问题包括：遗传和种群动态如何决定表型和进化多样性？如何将大规模精确数据转化为提高压力和病原体耐受性，以养活不断增长的世界人口，并制定干预措施，以减少环境变化、自然灾害和气候变化的速度和影响？定量建模如何才能产生高性能的分子、材料，并帮助预防野火和预测地震？UCR致力于这些问题的研究人员来自广泛的研究专业，包括环境科学、农业、生物、化学、物理、工程、计算机科学、统计学和应用数学。由于他们的研究在很大程度上依赖于高通量和计算建模方法，BD-HPC集群将允许使用新的计算方法来解决这些研究问题。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

项目成果

期刊论文数量（23）

专著数量（0）

科研奖励数量（0）

会议论文数量（0）

专利数量（0）

Anterograde signaling controls plastid transcription via sigma factors separately from nuclear photosynthesis genes.

DOI：
10.1038/s41467-022-35080-0
发表时间：
2022-12-02
期刊：
NATURE COMMUNICATIONS
影响因子：
16.6
作者：
Hwang, Youra;Han, Soeun;Yoo, Chan Yul;Hong, Liu;You, Chenjiang;Le, Brandon H.;Shi, Hui;Zhong, Shangwei;Hoecker, Ute;Chen, Xuemei;Chen, Meng
通讯作者：
Chen, Meng

Characterizing Protoclusters and Protogroups at z ∼ 2.5 Using Lyα Tomography

使用 LyÎ± 断层扫描表征 z ≤ 2.5 处的原簇和原群