REU Site: EXERCISE - Explore Emerging Computing in Science and Engineering

该奖项更新了马里兰州索尔兹伯里大学本科生运动研究经验（REU）网站。该网站的智力焦点是对并行计算新兴范例的研究。首席研究员将与导师一起指导一个为期10周的REU项目，该项目将为不同的学生提供并行计算领域的计算思维体验，并了解研究生院的经历。这些项目涵盖了并行计算的广泛领域，学生将在研究的各个方面获得经验。当多核和多处理器体系结构变得无处不在，越来越多的应用程序正在利用并行性时，强调并行计算是非常重要的。为了确保多样性，学生将从索尔兹伯里大学以及地区社区学院、马里兰大学东岸分校和其他历史上的黑人学院和大学中挑选。由于多核和多处理器体系结构的普遍存在，并行计算已成为计算科学的一个重要研究领域。然而，并行计算带来了一些挑战。在与进程交错相关的程序语义中存在一些基本困难：由于同时执行的任务之间不可预测的交互，并行程序可能产生不一致的答案，甚至崩溃。其次，通信、内存访问和I/O开销可能导致运行时延迟。最后，很难确保程序以同时实现效率和性能目标的方式消耗资源。基于上述挑战，REU站点将重点关注并行计算的四个方面，即算法、软件、架构和应用。学生将与教师导师一起完成尖端的研究项目，以解决强调上述四个方面的数据和计算密集型应用。在课程结束时，学生将获得宝贵的技能，对研究有更广泛和更深入的了解，并对自己的能力有更大的信心。特别是，他们将接触到并行计算的新兴范例，如MapReduce和GPU计算，并将有机会探索并发软件和多处理器架构，设计高效的并行算法，并解决计算机和社交网络，图像和信号处理以及地理信息系统中的数据和计算密集型问题。

This award renews the EXERCISE Research Experiences for Undergraduates (REU) Site at Salisbury University, Maryland. The intellectual focus of the site is research on emerging paradigms in parallel computing. The Principal Investigator, together with mentors, will supervise a 10-week REU program that gives a diverse cohort of students a taste of computational thinking in the domain of parallel computing and also an understanding of the graduate school experience. The projects cover a breadth of areas in parallel computing and the students will gain experience in all aspects of research. The emphasis on parallel computing is important particularly at a time when multicore and multiprocessor architectures are becoming ubiquitous and more and more applications are utilizing parallelism. To ensure diversity, students will be selected from within Salisbury University as well as from regional community colleges, University of Maryland Eastern Shore and other Historically Black Colleges and Universities. Because of the ubiquity of multicore and multiprocessor architectures, parallel computing has become an important area of research in computing science. However, parallel computing brings with it several challenges. There are fundamental difficulties in program semantics related to process interleaving: a parallel program can yield inconsistent answers, or even crash, due to unpredictable interactions between simultaneous tasks. Secondly, communication, memory access, and I/O overhead may result in run-time delays. Finally, it is difficult to ensure that programs consume resources in a manner that simultaneously achieves efficiency and meets performance goals. Based on the above challenges, the REU Site will focus on four aspects of parallel computing, namely, algorithms, software, architecture and applications. Students will work with faculty mentors in completing cutting-edge research projects to tackle data and compute intensive applications that emphasize the above four aspects. By the end of program, students will acquire valuable skills, gain a broader and deeper understanding of research, and develop greater confidence in their abilities. In particular, they will be exposed to emerging paradigms in parallel computing such as MapReduce and GPU computing, and will have opportunities to explore concurrent software and multiprocessor architectures, and design efficient parallel algorithms, and to tackle data and compute intensive problems in computer and social networks, image and signal processing, and geographic information systems.