MRI: Acquisition of Heterogeneous Computer System for Machine Learning

该奖项支持异构计算机系统的购买，部署和操作，以促进斯托尼布鲁克大学人工智能研究社区的许多教师的研究兴趣。共享的研究工具将使在许多领域的发现。举例来说：在地球科学领域，该集群将用于处理卫星图像，绘制北极和南极偏远地区的地图;在生物科学领域，该集群将用于建立神经网络，推动心脏图像和功能性磁共振成像研究;在社会科学领域，该集群将帮助开发能够阐明人口健康的社会和心理决定因素的方法和工具。在斯托尼布鲁克大学校园提供该仪器将大大有利于每年数百名学习机器学习和人工智能课程的研究生和本科生。拟议的集群将提供专业管理的资源，提供一个标准化的环境，并提供充分的技术支持。此外，学生需求预计将继续增长，通过几个正在进行的举措，包括本科计算机科学在人工智能的浓度，在自然语言处理和数据科学的新课程，最近批准的研究生计算机科学在数据科学的浓度，以及与文理学院（CAS）多个专业整合的“数据科学+X”本科序列。集群将由三类节点组成：（1）大型图形处理单元（GPU）机器，（2）具有大量内存的GPU服务器机器和（3）现场可编程门阵列（FPGA）机器，从而提供了一个前瞻性的计算环境，专注于支持人工智能的研究和实现。它将成为人工智能驱动的发现和创新研究所（AI Institute）的研究仪器催化剂，并大幅提升该机构的计算能力。这个系统？的异构性将允许具有优异性能的更通用的共享环境。将支持三个方向的研究：1）人工智能（AI），包括自然语言处理，计算机视觉和机器学习（ML）2）AI和ML在各种科学学科中的应用，包括生物医学信息学，化学，生态学和语言学，3）HPC的计算机科学（CS）研究，如可视化，神经网络编译和流程调度。此外，参与高中学生和教师，以及本科生和研究生的强有力的教育和推广活动有可能支持开发人员，研究人员，员工和用户的熟练劳动力的建设。该奖项反映了NSF的法定使命，并已被认为是值得通过使用基金会的智力价值和更广泛的影响审查标准进行评估的支持。

This award supports the purchase, deployment, and operation of a heterogeneous computer system to advance the research interests of many faculty in the Stony Brook University's Artificial Intelligence research community. The shared research instrument will enable discovery in a multitude of areas. For example: in Geosciences, the cluster will be used to process satellite imagery to map remote parts of the Arctic and Antarctic; in Biosciences it will be employed to build neural networks that will advance cardiac imagery and fMRI research; in Social Sciences it will help produce methods and tools that can illuminate social and psychological determinants of population health. The provisioning of the instrument in the Stony Brook University campus will greatly benefit hundreds of graduate and undergraduate students taking courses in machine learning and artificial intelligence each year. The proposed cluster will offer professionally-managed resources providing a standardized environment with adequate technical support. Further, student demand is anticipated to continue to grow through several ongoing initiatives including an undergraduate CS concentration in artificial intelligence, with new courses in NLP and data science, a recently approved graduate CS concentration in Data Science, and a proposed "Data Science+X" undergraduate sequence integrating with several majors in the College of Arts and Sciences (CAS).The cluster will comprise of three categories of nodes: (1) a large Graphics Processing Unit (GPU) machine, (2) GPU server machines with large amounts of memory and (3) Field Programmable Gate Arrays (FPGA) machines thus providing a forward-looking computing environment focused on supporting research on and enabled by AI. It will constitute the research instrumentation catalyst for the Institute for AI-Driven Discovery and Innovation (AI Institute) and significantly overhaul the compute capability of the institution. This system?s heterogeneity will allow for a more versatile shared environment with excellent performance. will support research in three directions: 1) Artificial Intelligence (AI) including Natural Language Processing, Computer Vision, and Machine Learning (ML) 2) applications of AI and ML on a variety of scientific disciplines including Biomedical Informatics, Chemistry, Ecology, and Linguistics, 3) Computer Science (CS) research on HPC such as visualization, neural network compilation, and process scheduling. Furthermore, the strong educational and outreach activities that engage high school students and teachers, as well as undergraduate and graduate students have the potential to support the building of a skilled workforce of developers, researchers, staff and users.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.