MRI: Acquisition of a Big Data Compute Cluster for Interdisciplinary Research

加州大学河滨分校 (UCR) 获得了一个高度可扩展的大数据计算集群，致力于为数据密集型 NSF 研究提供长期支持。通过释放和扩展目前超额预订的研究计算资源，拟议的计算集群将对研究生和本科生的培训和教育产生重大影响，其中包括传统上在 STEM 学科中代表性不足的人群。根据 URM 的入学情况，UCR 已被教育部指定为西班牙裔服务机构 (HSI)。充足计算的可用性及其对研究项目的有益影响将有助于吸引优秀学生参加大量本科和研究生项目，包括成功的 NSF 资助的 REU 和 IGERT 项目。与系统采购结合计划的新课程将培训学生并行计算概念，并提供将大数据计算集成到他们的研究项目中的扩展途径。该项目的大数据计算集群还将支持加州几家已经使用 IIG​​B 计算机设施的小型生物技术公司。来自外部研究机构、少数族裔服务大学和工业合作伙伴（特别是初创企业）的未来用户将被积极招募，以获得 IIGB 的计算资源。结合UCR的多元化种族和研究使命，这项投资将有利于UCR的广泛研究方向和基于技术的经济发展举措，UCR是加州内陆帝国经济发展的重要驱动力。该项目的目标是使UCR的大数据驱动研究能够在高度跨学科的环境中解决重大挑战问题。问题包括：不同的生物群体如何适应并防御极端环境条件或病原体？如何开发更高效、更具选择性的小分子来加速以发现为导向的化学生物学和基因组学研究？这些知识如何转化为改善胁迫和病原体耐受性，例如作物应对全球气候变化并养活不断增长的世界人口？高通量和监测技术的最新进展首次提供了新的方法来系统地、全面地、以前所未有的分辨率应对这些挑战。新的大数据计算集群大大增强了加州大学河滨分校的高性能计算基础设施，并为加州大学河滨分校研究人员提供了广泛的研究专业的关键支持资源，包括环境科学、化学基因组学、进化、统计学、计算生物学和多个生物组的基因组生物学。由于这项研究依赖于高通量和计算建模方法，因此其成功和未来的增长在很大程度上依赖于高性能计算机资源来管理和处理大型且快速增长的数据集。该系统将由综合基因组生物学研究所 (IIGB) 研究计算设施的经验丰富的人员进行管理。 IIGB 设施为分布在 50 多个研究小组各部门的广泛用户群体提供服务，拥有 160 名活跃用户。因此，所请求的计算系统将覆盖 UCR 的 NSF 资助的研究人员的最大数量，并构成 NSF 和 UCR 资金的具有成本效益的投资。

An award is made to the University of California, Riverside (UCR) to acquire a highly scalable Big Data compute cluster dedicated to long-term support for data-intensive NSF research. By freeing and expanding currently overbooked research compute resources, the proposed compute cluster will have a significant impact on training and educating graduate and undergraduate students, including a high percentage from populations traditionally underrepresented in STEM disciplines. Based on URM enrollment, UCR has been designated by the Dept. of Education as an Hispanic Serving Institution (HSI). The availability of adequate computing and its beneficial impact on research programs will serve to attract outstanding students to a large number of undergraduate and graduate programs, including successful NSF-Funded REU and IGERT programs. New courses planned in conjunction with system acquisition will train students in parallel computing concepts and offer expanded access to integrate Big Data computing into their research projects. The Big Data compute cluster of this project also will support several smaller biotechnology companies in California that already use IIGB's computer facility. Future users from external research institutions, minority-serving colleges and industrial partners, particularly start-ups, will be actively recruited to gain access to IIGB's computing resources. Combined with UCR's diverse ethnicity and research mission, this investment will benefit a wide array of research directions and technology-based economic development initiatives at UCR, an institution that serves as an important driver of economic development in California's Inland Empire.The goal of this project is to enable Big Data driven research at UCR to address grand challenge questions in a highly interdisciplinary environment. Questions include: How do different organism groups adapt to, and defend themselves against extreme environmental conditions or pathogens? How can more efficient and selective small molecules be developed to accelerate discovery-oriented chemical biology and genomics research? How can this knowledge translate into improved stress and pathogen tolerance, for example in crops to respond to global climate change and feed a growing world population? Recent advances in high-throughput and monitoring technologies offer, for the first time, novel methods to address these challenges systematically, comprehensively, and with unprecedented resolution. The new Big Data compute cluster substantially strengthens UCR's high-performance compute infrastructure and provides a critical enabling resource for UCR researchers from a broad spectrum of research specializations, including environmental science, chemical genomics, evolution, statistics, computational biology, and genome biology of multiple organism groups. Since this research relies on high-throughput and computational modeling approaches, its success and future growth is critically dependent on high-performance computer resources to manage and process large and rapidly increasing data sets. The system will be managed by experienced personnel in the Research Compute Facility of the Institute for Integrative Genome Biology (IIGB). The IIGB facility serves a broad user population distributed across departments from more than 50 research groups with 160 active users. The requested computing system therefore will reach a maximum number of NSF-funded investigators at UCR and constitutes a cost-effective investment of NSF and UCR funds.