Research Infrastructure: CC* Data Storage: 20 Petabyte Campus Research Storage Facility at Johns Hopkins University

约翰霍普金斯大学(JHU)有一系列正在进行的研究项目，这些项目产生并分析了数PB的数据。其中包括来自广泛领域的大型数值模拟(湍流、宇宙学、海洋环流模型)和大型显微数据(低温电子显微镜、荧光显微镜、材料科学项目、NG测序)，以及来自数字社会科学的各种大型数据融合项目。过去十年来，JHU数据密集型工程与科学研究所一直在为这些活动提供支持，提供了一个平台，在JHU内外的所有学科中高速存储和服务PB级数据。2022年夏天在JHU举办了一次研讨会后，对新的更大规模、校园范围的研究存储设施的需求变得明显起来。该CC*项目在NSF之前投资的基础上，以非常经济高效的方式为大数据项目构建了一个30PB的数据设施。该系统基于升级90节点数据范围集群，其SuperMicro机箱和电源都是标准化的，并与最新的主板和CPU兼容。这些节点以较低的每节点成本升级到AMD Ryzen系统，并转变为具有30PB净存储容量的高性能Cave集群。新的存储服务于非常广泛的科学研究，包括为全球科学提供数PB的开放科学数据，包括SDSS、湍流、海洋环流和宇宙学模拟。这一奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

There is a wide spectrum of ongoing research projects at Johns Hopkins University (JHU) that generate and analyze many petabytes of data. These include both large numerical simulations (turbulence, cosmology, ocean circulation models) and large microscopy data from a broad range of areas (cryoEM, fluorescent microscopy, material science projects, NG sequencing) and various large-scale data fusion projects from digital social science. The JHU Institute for Data Intensive Engineering and Science has been supporting these activities for the last decade by providing a platform to store and serve petabytes at high speeds and at excellent economies of scale across all disciplines at JHU and beyond. After a workshop held at JHU in the summer of 2022 the need for a new larger-scale, campus-wide research storage facility became clear.This CC* project builds a 30PB data facility for Big Data projects, in a very cost-effective way, building on previous NSF investments. The system is based on upgrading the 90-node Data-Scope cluster whose Supermicro chassis and power supplies are standardized and compatible with the latest motherboards and CPUs. These nodes are upgraded at a low per node cost to a AMD Ryzen system and turned into a high-performance Ceph cluster with 30PB net storage capacity. The new storage serves a very wide range of scientific research, including offering many petabytes of open scientific data for global science including SDSS, turbulence, ocean circulation, and cosmology simulations.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.