Collaborative Research: GOALI Statistical Methods for Modern IT Systems

在数据中心/超级计算机热管理和商业操作模拟等IT行业实际问题的激励下，研究人员旨在为现代IT系统的实验规划、建模和优化开发一套新颖的统计方法。具体来说，他们为具有高维响应、具有空间和时间响应或具有大量配置变量的IT系统，以及用于业务操作模拟的实验规划和优化，提出了新的建模技术。研究人员汇集了计算机建模和实验、潜在变量和结构方程模型、现代优化和实验设计方面的专业知识。他们的研究将弥合学术界和工业界统计实践之间的差距。他们将使用IBM具有挑战性的现实问题来激励和开发新的方法，并在实际数据上对其进行测试以进行改进。它的智力价值在于开发了一种通用的方法，用于设计、建模和优化IT或其他系统，这些系统表现出与上面描述的相似的特征。它可以在多元统计建模、随机过程建模、统计辅助随机优化、优化辅助设计搜索和空间填充设计方面取得重大进展。可以想象，该方法可以合并到公开发布的软件中，从而直接使从业者和研究人员受益。许多新的IT系统（如超级计算机、数据中心和存储系统）已经被发明出来，以适应不同的业务和个人需求。IT行业最近的一个趋势是将硬件中的传统业务与企业IT服务（如web托管、数据存储和高性能计算）集成在一起。拟议的工作预计将对一般复杂系统的设计、监测和管理产生广泛的影响。它可以应用于各种各样的问题，如电力系统和飞机发动机燃烧室。它还有助于为气候变化、对自然危机的反应以及禽流感和SARS等流行病的传播建立大规模计算机模型。具体来说，开发的方法可以提高电子系统的热管理和冷却效率，这是当今许多美国工业面临的紧迫问题。该小组致力于教育和传播新方法，以产生长期影响。他们计划将研究成果融入到课程作业中。拟议的教育计划将严格培养一批在统计方法、不确定性下的决策和计算建模方面具有扎实背景的多样化学生，他们将满足IT和其他高科技产业的关键需求。他们致力于在他们的研究小组中创造一个种族、性别和国籍多样化的环境。

Motivated by real problems in the IT industry like data center/supercomputer thermal management and simulations of business operations, the investigators aim to develop a set of novel statistical methods for the experimental planning, modeling, and optimization of modern IT systems. Specifically, they propose new modeling techniques for IT systems with high-dimensional responses, with spatial and temporal responses, or with a large number of configuration variables, and for the experimental planning and optimization of business operation simulations. The investigators bring together expertise in computer modeling and experiments, latent variable and structural equation models, modern optimization, and design of experiments. Their research will bridge the gap between statistical practice in academe and industry. They will use challenging real-world problems at IBM to motivate and develop new methodologies, and in turn test them on real data for improvement. Its intellectual merit lies in the development of a general methodology for designing, modeling, and optimizing IT or other systems which exhibit similar traits to those described above. It can lead to major advances in multivariate statistical modeling, stochastic process modeling, statistics-aided stochastic optimization, optimization-aided design search, and space-filling designs. It is conceivable that the methodology can be incorporated into publicly released software, thus directly benefiting practitioners and researchers. Many new IT systems like supercomputers, data centers, and storage systems have been invented to accommodate different business and personal needs. A recent trend in the IT industry is the integration of the traditional business in hardware with enterprise IT services like web hosting, data storage, and high-performance computing. The proposed work is expected to have broad-based impacts on the designing, monitoring and management of complex systems in general. It can be applied to a variety of problems like power systems and aircraft engine combustors. It can also benefit large-scale computer modeling for climate change, reaction to natural crisis, and the spread of pandemic diseases like bird flu and SARS. Specifically, the developed methods can improve the thermal management and cooling efficiency of electronic systems, which is a pressing issue faced by many US industries today. The team is committed to education and dissemination of the new methodology to make a long-term impact. They plan to infuse research outcomes into coursework. The proposed education plan will result in rigorous training of a diverse group of students with solid background in statistical methods, decision-making under uncertainty, and computational modeling, who will meet a critical need of IT and other high-tech industries. They are committed to creating a diverse environment in their research groups in terms of race, gender and national origin.