MRI: Acquisition of an Adaptive Data Cluster for Data-intensive Applications in Science and Engineering

该项目旨在为多个研究领域提供服务，如基因组学、生物信息学、计算机安全、数字人种学、环境建模和计算机科学。灵活的存储包括具有集成计算能力的集成多PB磁盘系统，以及用于数据和存储密集型应用程序的可扩展磁带归档系统。该系统允许在存储节点上直接执行I/O受限计算(与传统存储群集不同)，还可以充当具有海量带宽的分布式文件系统，以允许CPU受限计算受益于现有群集计算资源(与典型的Hadoop群集不同)。该仪器能够-在基因组建模、超提取经济和表型鉴定方面更深入地观察-带来与计算资源相关的更大数据容量，-应对重大挑战(例如，预测生态系统对自然和人为全球和区域变化的反应)。-在高通量表型鉴定、计算机安全和基因组注释方面开发新算法(从而利用混合平台实现新的科学)。因此，存储集群构成关键需求的开创性组件，不仅在机构，而且在整个州，为数据沉浸式计算提供基于校园的设施，因为该机构目前还没有具备“大数据”高端计算能力的中央设施。随着新算法的开发，以更好地对网络交互进行建模，从而提高金融和网络基础设施的能力、弹性和抵抗力，可能会感受到对网络安全研究的多学科影响。它还可以帮助培训新一代研究人员关于数据密集型计算的工具和技术，并在他们的研究需要超过当地资源时，方便他们向XSEDE迁移。当开发出更好的水、生态和经济因素相互作用的模型时，可以为保护环境做出贡献。此外，它还可以加强和整合K-12、本科生和研究生在生物信息学方面的教育努力(例如，编写教材，影响K-12和STEM教育，如‘这是一场爆炸’，以及为女高中生发展讲习班)。最终，它允许进入社区大学和非博士授予机构，通过EPSCoR州扩展大数据，使许多研究人员和教育工作者能够。

This project, acquiring an adaptive multi-petabyte scalable storage cluster for high-end applications, aims to service multiple research areas such as: genomics, bioinformatics, computer security, digital ethnography, environmental modeling, and computer science. The flexible storage consists of an integrated multi-petabyte disk system with integrated compute capabilities and a scalable tape archive system for data and storage intensive applications. The system allows I/O-limited calculations to be performed directly on the storage nodes (unlike the traditional storage clusters) and can also act as a distributed file system with massive bandwidth to allow CPU-limited calculations to benefit from existing cluster computational resources (unlike typical Hadoop clusters). The instrument enables - Looking deeper in modeling genomes, hyper-extractive economies and phenotyping- Bringing greater data capacity tied to computational resourcing,- Attacking grand challenges (e.g., forecasting responses of ecological systems to natural and anthropogenic global and regional change).- Developing new algorithms in high-throughput phenotyping, computer security, and genome annotation (hence enabling a new science with the hybrid platform).Thus, the storage cluster constitutes a seminal component for a critical need, a campus-based facility for data immersive computing, not only at the institution, but for the entire state, since the institution currently does not have a central facility with capability for 'big data' high-end computing. As new algorithms are developed for better modeling cyber interactions that can lead to increase the financial and network infrastructure's ability, resiliency, and resistance, multidisciplinary impacts on cybersecurity research are likely to be felt. It can also contribute to train a new generation of researchers in tools and techniques for data-intensive computing and ease their migration to XSEDE when their research needs exceed the local resources. It can contribute to protect the environment when developing better models of the interaction of water, ecology, and economic factors. Moreover, it can enhance and integrate educational efforts at the K-12, undergraduate, and graduate levels in bioinformatics (e.g., preparation of educational materials, impacting the K-12 and STEM education such as 'It's a BLAST' and GROW workshops for female high school students). Ultimately, it allows access to community colleges and non-PhD granting institutions to extend big data through and EPSCoR state, enabling many researchers and educators.