REU Site: Undergraduate Research Experiences in Computer Systems at University of Louisville

路易斯维尔大学将建立一个本科生研究经验（REU）网站，在为期10周的夏季会议中，在全国范围内接待不同的本科生，与教师导师一起进行与计算机系统相关的主题的研究，包括操作系统、并行和分布式系统、嵌入式系统、移动系统和计算机体系结构。除了拟议的研究项目的显著更广泛的社会影响外，这个REU网站将影响来自研究机会有限的学校的本科生，帮助他们获得计算机系统的理论和实践知识，培训他们进行尖端的计算机系统研究，并激励他们继续攻读计算机科学的研究生教育。摩尔定律的终结是探索未来新计算机系统设计的一个激动人心的时刻。该REU网站包括广泛的计算机系统研究主题，从处理器架构到存储系统，从小型系统（如移动和边缘设备）到大型系统（包括百亿亿次数据中心）。研究项目将通过探索移动和边缘设备上新兴应用的新架构、操作系统的节能存储堆栈设计、节能嵌入式系统和微控制器、数据密集型和高性能计算的新软件工具、新的图形分析算法、物联网应用的整体安全解决方案、新颖的分布式和可解释的机器学习算法，推动计算机系统的最新发展。新的量子加速技术，以及用于生物信息学应用的新型GPU支持并行文档反转算法。采用多层次的指导模式，每周与项目负责人会面，每天与导师会面，并与研究生持续互动。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

The University of Louisville will establishes a Research Experiences for Undergraduates (REU) Site to host a diverse cohort of undergraduate students across the nation in 10-week summer sessions to conduct research with faculty mentors on topics related to computer systems, including operating systems, parallel and distributed systems, embedded systems, mobile systems, and computer architecture. In addition to the significant broader social impacts of the proposed research projects, this REU site will impact undergraduate students from schools with limited research opportunities by helping them gain theoretical and practical knowledge in computer systems, training them in conducting cutting-edge computer systems research and inspiring them to pursue postgraduate education in computer science.The end of Moore's Law is an exciting time to explore new computer system designs for the future. This REU Site includes a broad range of computer systems research topics, ranging from processor architecture to storage systems and from small-scale systems such as mobile and edge devices to large-scale systems including exascale data centers. Research projects will advance the state-of-the-art in computer systems by exploring new architectures for emerging applications on mobile and edge devices, energy-efficient storage stack designs for operating systems, energy-efficient embedded systems and microcontrollers, new software tools for data-intensive and high-performance computing, new graph analytics algorithms, holistic security solutions for IoT applications, novel distributed and explainable machine learning algorithms, new quantum acceleration techniques, and novel GPU enabled parallel document inversion algorithms for bioinformatics applications. A multi-level mentoring model will be followed through weekly meetings with the PIs, daily meetings with the mentors, and continuous interaction with graduate students.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.