REU Site: High Performance Filesystems and Data Visualization

对黑洞和星系合并等星系事件的模拟使科学家能够了解宇宙的基本性质。这些模拟产生了数TB的数据，使用传统的数学工具和技术分析这些数据极其困难和耗时。为了应对这些挑战，科学家们经常使用数据可视化，它提供了一种强大而有效的方法来了解相互作用和模拟的行为，例如可视化超大质量黑洞合并期间引力波的辐射。可视化系统需要高性能的文件系统来实现高效的数据管理。在过去的三年里，计算机科学系和罗切斯特理工学院计算相对论和引力中心的合作产生了一个名为Spiegel的可视化框架，该框架已成功地用于分析和可视化各种银河系事件的模拟。该REU网站为学生提供机会、环境和支持，以Spiegel为起点进行数据可视化和高性能文件系统的研究。在协作和跨学科的环境中工作，学生在对海量多维数据进行计算时开发解决方案来解决广泛的研究问题。因此，学生在理解、评论和呈现研究文献方面获得了知识。这个项目为学生提供了学习最先进的计算技术的机会，这些技术对于解决现代科学学科中的研究问题越来越重要。鼓励本科生攻读STEM学科的跨学科研究生课程。通过针对妇女、少数民族和残疾人等代表性不足的群体，特别是聋哑人和听力障碍学生的具体招聘工作，这一REU计划还旨在增加科学劳动力的规模和多样性。

Simulations of galactic events such as black hole and galaxy mergers allow scientists to understand the fundamental nature of the universe. These simulations create terabytes of data, which are extremely difficult and time consuming to analyze using traditional mathematical tools and techniques. To address these challenges, scientists often use data visualization, which provides a powerful and effective approach to understand interactions and behavior of simulations such as visualizing the radiation of gravity waves during a supermassive black hole merger. Visualization systems require high performance file-systems for efficient data management. Over the last three years, a collaborative effort between the Computer Science Department and the Center for Computational Relativity and Gravitation at Rochester Institute of Technology resulted in a visualization framework called Spiegel that has been used successfully to analyze and visualize the simulation of a variety of galactic events.This REU site provides students with the opportunity, environment and support to conduct research in data visualization and high-performance file systems using Spiegel as the starting point. Working in a collaborative and interdisciplinary environment, students develop solutions to a broad set of research problems in performing computation on massive amounts of multi-dimensional data. Consequently, students gain knowledge in understanding, critiquing, and presenting research literature. This project offers students opportunities to work on state-of-the-art computing techniques that are increasingly vital for solving research problems in modern scientific disciplines. Undergraduate students are encouraged to pursue interdisciplinary graduate studies in STEM disciplines. With specific recruiting efforts that target underrepresented groups such as women, minorities, and persons with disabilities, especially deaf and hard-of-hearing students, this REU program also aims to increase the size and diversity of the scientific workforce.