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.

授予加利福尼亚大学河滨分校（UCR）获得大数据高性能计算（BD-HPC）集群，旨在实现与环境和社会高度相关的新颖和变革性研究，外展和培训活动。该系统将由UCR的HPC中心（HPCC）管理，该中心服务于跨大学和部门分发的广泛而多样化的用户群体。作为一种高度共享的资源，该工具将启用大量NSF资助的计划，包括旨在改善一致，环境保护，技术发展和行业的实践的计划。广泛的教育和培训活动被整合到传播大数据科学的多学科概念。这些宣传组成部分将教育公众关于大数据科学对环境，经济和社会的影响。 HPCC支持许多本科生和毕业生。在各种学科中的课程。它的资源也有助于在各种数据科学领域开发新课程和计划。这些课程和课程中很大一部分的学生来自STEM学科中传统上代表性不足的人群。足够的计算及其对教育计划的有益影响将吸引杰出的学生参加计算和定量的本科和研究生课程。结合UCR的潜水种族和研究任务，这项投资将使一系列翻译的研究方向和基于技术的经济发展计划受益。新的BD-HPC集群将实现无法对UCR当前的研究计算基础设施或社区Cyberinfratucture（CI）进行的新型研究，同时还可以提供足够的能力，以提供足够的能力，以提供足够的能力，可以为进步的研究提供了足够的支持。当前和新的研究都解决了高度跨学科的环境中的基本问题，该环境在基础和翻译研究中桥接了各种各样的科学和工程学科。提出的大挑战问题包括：遗传和人口动态如何确定表型和进化多样性？如何将大规模的精度数据转化为改善压力和病原体的耐受性，以养活不断增长的世界人群，并开发干预措施以降低环境变化，自然灾害和气候变化的速度和影响？定量建模如何导致高性能分子，材料并有助于预防野火并预测地震？从事这些问题的UCR研究人员来自广泛的研究专业，包括环境科学，农业，生物学，化学，物理，工程，工程，计算机科学，统计和应用数学。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，因此BD-HPC群集将允许新的计算方法来解决这些研究问题。该奖项反映了NSF的法定任务，并通过使用基金会的知识分子优点和更广泛的影响审查标准来通过评估来诚实地表示支持。

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