CC* Compute: Private Campus Cloud for Data Analytics and Machine Learning

点击翻译按钮获取中文摘要

New usage patterns of computing for research have emerged that rely on the availability of flexible, elastic, and highly specialized services. Uniform batch computing pools traditionally provided by high performance or high throughput computing environments have difficulty adapting to meet these requirements. A new approach that updates and evolves the research computing ecosystem is needed to respond to these needs. This new model, a “Community Cloud”, provides a cost effective, highly responsive, sustainable, and customizable cloud and container computing solutions for specific applications and domain science communities.This project, through the acquisition of a new compute cluster, knits together central and lab-scale data, instrument, and compute resources into a cloud ecosystem for researchers who need capabilities beyond batch computing, and extends the research computing ecosystem to include cloud capabilities at the campus level. The Community Cloud is designed to: 1) Devise a new approach to establish a community cloud service using virtualization, containers, and infrastructure-as-code (IAC) techniques to create running infrastructure as an artifact; 2) Support diverse science domains via an effective infrastructure that enables new kinds of discovery that cannot be well met through the use of traditional batch computing systems; 3) Develop a reference business model for the evolution of campus “condo” cluster programs to sustainably operate a production community cloud; and 4) Enable scalable and sustainable instructional use of the proposed community cloud for courses, real-world training, and workforce development for the campus and national research computing communities. The new compute cluster includes 8 application nodes (1024 cores), 2 GPU nodes (8 gpus), 6 storage nodes (288 TB), and one bastion node, all interconnected through a 100Gb network, and managed using Kubernetes.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.