MRI: Acquisition of High Performance Computing and Data Visualization for Scientists and Engineers

该项目从EPSCoR状态开始，通过升级当前的RCF机器增加了新的可视化功能，为广泛的用户群提供高性能资源和培训。基础设施是目前容量和内存的两倍，为分布在四个校区的15个部门提供服务。这个SGI工具提供给用户的共享内存为需要大量处理器间通信的算法提供了合适的体系结构。可视化功能允许研究人员在自己的显示器上查看动画或图形输出，从而可以远程工作。可视化功能使多达16名研究人员能够从远程站点同时进行交互，从而增强远程协作和教育推广。研究活动包括：网格计算、中间件研究、纳米尺度原子计算机模拟、中尺度气象建模、道路安全基因组研究——车辆耐撞性建模，以及减少芯片系统的设计测试周期。该大学将利用基础设施来增强多样性。

This project from an EPSCoR state, adding a new visualization capability by upgrading current RCF machine, provides high performance resources and training to a broad user base. The infrastructure doubles the current capacity and memory, servicing 15 departments distributed over four campuses. The shared-memory presented to the user by this SGI instrumentation provides a suitable architecture for algorithms that require large amounts of inter-processor communication. The visualization feature allows researchers to view animation or graphical output on their own display, making it possible to work remotely. The visualization capability enables up to 16 researchers to interact simultaneously from remote sites, thus enhancing distance collaboration and educational outreach. Research activities involve: Grid Computing, Middleware Research, Atomistic Computer Simulation for the Nanoscale, Mesoscale Meteorological Modeling, Genome Research Roadway Safety - Modeling Vehicle Crashworthiness, and Reducing the Design-Testing Cycle in Systems on a Chip.The university will use the infrastructure to enhance diversity.