MRI: Acquisition of a Hybrid GPU Computing Cluster High-End Applications in Science and Engineering

MRI：收购混合GPU计算集群 科学与工程高端应用

• 批准号: 1126709
• 负责人: Daniel Andresen
• 金额: $ 70万
• 依托单位: Kansas State University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2011
• 资助国家: 美国
• 起止时间: 2011-09-01 至 2014-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1126709&HistoricalAwards=false
• 关键词: MRI; Acquisition; Hybrid; GPU; Computing

Proposal #: CNS 11-26709PI(s): Andresen, Daniel; Caragea, Doina; Dodds, Walter K; Esry, Brett; Steward, David R. Institution: Kansas State UniversityTitle: MRI/ Acq.: A Hybrid GPU Computing Cluster High-End Applications in Science and EngineeringProject Proposed:This project, acquiring a hybrid computing cluster for high-end applications in science and engineering, services, among others, bioinformatics, ecological modeling, and physics. GPU-based computing support for distributed memory parallel applications constitutes a specific novel feature of the cluster.The work aims to support the following activities:- Modeling genomes, hyper-extractive economies, and ecological forecasting (by bringing much greater computational power) and,- Enabling new science utilizing the instrument to develop new algorithms in physics modeling and genomics. Broader Impacts:Mainly, the multidisciplinary nature of the proposed research provides the broader impacts. Expected are large broader impacts on basic physics research. It is expected to also impact on medicine through the development of better molecular models to view how our proteins and membranes interact. Planned are training activities of a new generation of researchers in tools and techniques for high-performance computing. The PIs would build on the broad past experience in preparing widely-used undergraduate and graduate educational materials, allowing students to perform real-world projects and impacting K-12 and STEM education. Hence, the project aims to significantly enhance and integrate our educational efforts at the K-12, undergraduate and graduate levels in bioinformatics.

提案#:CNS 11-26709PI(s): Andresen, Daniel；Caragea);多德，沃尔特·K；Esry,布雷特;Steward, David R.机构：堪萨斯州立大学头衔：MRI/ Acq。项目建议：该项目将收购一个混合计算集群，用于科学和工程、服务等领域的高端应用，其中包括生物信息学、生态建模和物理。对分布式内存并行应用程序的基于gpu的计算支持构成了集群的一个特定的新特性。这项工作旨在支持以下活动：-基因组建模、超采掘经济和生态预测（通过带来更大的计算能力），以及-利用该仪器开发物理建模和基因组学新算法的新科学。更广泛的影响：主要是，拟议研究的多学科性质提供了更广泛的影响。预计将对基础物理研究产生更广泛的影响。它还有望通过开发更好的分子模型来观察我们的蛋白质和膜如何相互作用，从而对医学产生影响。计划对新一代研究人员进行高性能计算工具和技术方面的培训活动。pi将建立在广泛使用的本科和研究生教育材料的广泛过去经验的基础上，允许学生执行现实世界的项目，并影响K-12和STEM教育。因此，该项目旨在显著加强和整合我们在K-12、本科和研究生阶段的生物信息学教育工作。