Acquisition of a High Performance Computer Cluster for Atmospheric Modeling

根据这项主要研究仪器奖，首席研究员将获得一个高性能计算机集群，用作内华达州大学大气科学部（DAS）内中尺度动力学和数值模拟组的主要计算资源。 DAS的研究范围最近扩大，包括两个国家科学基金会资助的项目，重点是中尺度大气现象和中尺度数值模拟，导致迫切需要专门的计算资源，以更好地支持目前和计划中的研究活动。 购置一个32节点计算机集群将是DAS研究基础设施的一个重大和具有成本效益的扩展。 这样一个专用的高速计算平台将以商用超级计算机的一小部分成本提供超级计算机的性能，并且对于数值模拟小组和相关学生继续进行旨在改善当前和未来项目中数值天气预报的竞争性研究至关重要。研究生研究培训是DRI研究企业的重要组成部分。 所要求的设备将提供一个环境，广泛培训学生追求高级学位的大气科学计划。 它将促进计算机和大气科学部门之间更密切的合作。 从长远来看，该设备预计将为跨学科合作提供一个焦点，特别是促进内华达州大学在地球科学中更广泛地采用高性能并行计算。

Under this Major Research Instrumentation award the Principal Investigator will acquire a high-performance computer cluster to be used as the primary computational resource for the mesoscale dynamics and numerical modeling group within the Division of Atmospheric Sciences (DAS) at the University of Nevada. The recent expansion of DAS's research scope including two National Science Foundation funded projects focusing on mesoscale atmospheric phenomena and mesoscale numerical modeling has led to an immediate need for dedicated computational resources to better support present and planned research activities. The acquisition of a 32-node computer cluster will be a significant and cost-effective expansion of the research infrastructure at DAS. Such a dedicated, high-speed computing platform will provide supercomputer performance at a fraction of the cost of a commercial supercomputer, and is crucial for the numerical modeling group and associated students to continue to conduct competitive research aimed at improving numerical weather forecasting within current and future projects.The graduate student research training is an important part of the research enterprise at DRI. The requested equipment will provide an environment to extensively train students pursuing advanced degrees in the Atmospheric Sciences Program. It will foster a closer collaboration between the Computer and Atmospheric Science Departments. In the long term, the equipment is expected to provide a focal point for interdisciplinary collaboration and, especially, facilitate a wider adoption of high-performance parallel computing in earth sciences at the University of Nevada.