CC* Compute: Interactive Data Analysis Platform

莱斯大学从事开创性数据密集型科学和工程的研究人员越来越依赖于他们研究所需的实时数据分析设施。这些研究活动包括图像处理、计算机视觉和机器学习，跨越多个领域，如地质科学、统计学、计算机科学和物理学。这些问题领域或用例都可以通过利用GPU加速器进行交互式计算的共享计算基础设施来解决。该系统不仅为科学研究提供了重要的资源，而且还通过研究计算中心的外展，为下一代计算科学家提供了最新gpu计算技术的教育。该资源包括9个计算节点，每个计算节点具有40核，384GB RAM， 4TB NVMe存储和8个NVIDIA Quadro RTX 6000 gpu。这些系统通过高性能网络相互连接，并托管在Science DMZ上，将它们与开放科学网格以及商业云集成在一起，从而增加了作为国家OSG努力的一部分的利用率，并能够利用云资源进行负载爆发。该系统利用开源软件栈来支持容器化，使每个研究人员能够利用他们自己独特的软件和工具包，同时共享公共硬件和公共云访问平台。此外，基础设施是一个更大的技术生态系统的一部分，该系统利用联合身份和访问管理作为InCommon的一部分，与科学DMZ的高级网络，以及信息安全办公室，不仅支持大学数据和技术安全，还包括针对研究数据和协议安全的目标扩展。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

Rice University researchers engaged in groundbreaking data-intensive science and engineering increasingly depend on access to real-time data analysis facilities required for their research. These research activities include image processing, computer vision, and machine learning, spanning multiple fields, such as geological sciences, statistics, computer science, and physics. Each of these problems areas or use cases can be addressed by shared computational infrastructure leveraging GPU accelerators for interactive computing. The system provides a significant resource for enabling science but also for educating the next generation of computational scientists in the latest GPU-computing techniques through the outreach of the Center for Research Computing. The resource includes nine compute nodes, each with 40 cores, 384GB RAM, 4TB NVMe storage, and 8 NVIDIA Quadro RTX 6000 GPUs. The systems are interconnected via high-performance networking and hosted on a Science DMZ integrating them with the Open Science Grid as well as commercial cloud allowing both increased utilization as part of national OSG efforts and the ability to utilize cloud resources for load bursting. The system leverages an open-source software stack designed to support containerization, enabling each researcher to utilize their own unique set of software and toolkits while sharing common hardware and a common cloud access platform. Moreover, the infrastructure is part of a larger technology ecosystem that leverages federated identity and access management as part of InCommon, advanced networking with science DMZ, and Information Security Office that supports not only university data and technology security but includes targeted outreach for research data and protocol security.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.