MRI: Acquisition of High Performance Computing Instrument for Collaborative Data-Enabled Science

提案号：12-28312PI(s): Apon, Amy W. Gemmill, Jill；利根，沃尔特·B.；史密斯，梅丽莎C.；机构：克莱姆森大学头衔：MRI/Acq。项目建议：该项目为协作数据科学获取高性能计算（HPC），旨在实现实验HPC领域的基础和应用研究，包括可扩展文件系统、加速器技术、中间件架构和集群调度策略。该仪器将作为一种生产资源，用于支持材料和生物分子建模、生物信息学（以及其他）方面的几个引人注目的科学应用，并将为该机构贡献重要的新组成部分。它建立和管理良好的Palmetto集群，同时提供急需的文件存储和加速器系统，目前还不可用。支持的项目包括：-可扩展文件系统实现，-异构计算环境中的并发性开发和分析，-高性能集群建模，分析和表征，-文件复制和一致性维护，-云架构，-先进材料和生物分子系统的特性，-多点的分子动态模拟研究，新型发光纳米粒子、生物分子进化、优化水直接化学修复的催化剂、蛋白质表面相互作用、下一代测序数据组装的Map/Reduce框架、寻找显著保守蛋白块的识别、数字制造、非参数生产模型的统计推断、医院和银行业结构分析、多重散射渲染、数字奖学金、-计算在地球科学中的应用。预期科学小组定期计划的投入将有助于制定政策，以便将该仪器用作实验性高性能计算系统研究的试验台，以及用于科学应用的共享生产资源。更广泛的影响：该仪器作为协作团队的工具，包括来自4个机构的20多名教师，以及250多名研究生和本科生。该系统也将被已经建立的？桌面转泰瑞格？该项目覆盖了EPSCoR州南卡罗来纳的十多所大学，并与地区合作伙伴合作。提案小组包括6名妇女高级人员。该机构有外展、教育和培训活动，并已聘请SC？它是该地区唯一的公立HBCU，南卡罗来纳州立大学以及其他少数族裔机构。跨学科课程的发展将支持计算和数据驱动的科学和工程。

Proposal #: 12-28312PI(s): Apon, Amy W. Gemmill, Jill; Ligon, Walter B.; Smith, Melissa C.; Stuart, Steven J.Institution: Clemson UniversityTitle: MRI/Acq.: High Performance Computing Instrument for Collaborative Data-Enabled ScienceProject Proposed:This project, acquiring a high performance computing (HPC) for collaborative data-enabled science, aims to enable fundamental and applied research in areas of experimental HPC, including scalable file systems, accelerator technologies, middleware architectures, and cluster scheduling policies. The instrument will be used as a production resource to support several compelling science applications in materials and biomolecular modeling, bioinformatics (and others) and will contribute a significant new component of the institution?s well established and managed Palmetto cluster while providing critically needed file storage, and accelerator systems not currently available. Supported projects include:- Scalable file system implementation,- Exploiting and analyzing concurrency in heterogeneous computing environments,- High performance cluster modeling, analysis, and characterization,- File replication and consistency maintenance,- Cloud architecture,- Properties of advanced materials and biomolecular systems,- Molecular dynamic simulation studies of poly-dots, new light-emitting nanoparticles,- Biomolecular evolution,- Optimizing catalysts for direct chemical remediation from water,- Protein-surface interactions,- Map/Reduce framework for next generation sequencing data assembly,- Searching for identification of significantly conserved protein blocks,- Digital manufacturing,- Statistical inference in nonparametrics models of production,- Analysis of the structures of hospital and banking industries,- Multiple scatter rendering,- Digital scholarship, and- Applications of computing to the geosciences.Regular planned input from the scientific team is expected to facilitate the development of policies for use of the instrument as a test bed for experimental high performance computing systems research as well as a shared production resource for scientific applications.Broader Impacts: The instrument serves as a tool for the collaborative team that includes more than 20 faculty from 4 institutions, and more than 250 graduate and undergraduate students. The system will also be utilized by the already established ?Desktop to Teragrid? program that reaches more than a dozen universities across South Carolina, an EPSCoR state, and with regional partners. The proposal team includes 6 women senior personnel. The institution has outreach, education, and training activities, and has engaged SC?s only public HBCU, South Carolina State University, as well as other minority institutions within the region. Development of interdisciplinary curricula will support computational and data-enabled science and engineering.