CRI: IAD: A Service-Oriented Architecture for The Computation, Visualization, and Management of Scientific Data

现在，先进的计算能力对于解决科学和工程中的复杂问题至关重要。计算机模型已经成为基础研究的基础。它们在以现实的细节处理被建模的物理系统的微妙参数方面越来越有用。在计算机模型日益相关的基础上，是可用的低成本计算能力的巨大且相对较新的增长。计算能力以及计算机建模和模拟方面的这些进步带来了科学计算的新兴领域，来自多个学科的科学家和工程师合作了解各种复杂的系统，这些系统在几年前还无法达到。这个基础设施项目在纽约理工大学建立了用于科学可视化的高分辨率显示墙，在犹他大学科学计算和成像研究所(SCI Institute)建立了基于GPU的高性能计算集群。这一独特的资源使科学家能够在协作环境中高效地进行日益复杂的科学计算和可视化。该基础设施使研究能够高效地执行模拟；简化复杂数据产品的创建；产生高质量的可视化；以及科学的工作流程，从而简化设计模拟和分析其结果的过程。该项目有可能影响目前科学数据的计算、可视化和管理成为瓶颈的各种应用。通过我们的跨学科合作，这个项目将在帮助改进科学发现过程方面产生立竿见影的效果。研究生和本科生参与该项目将提供指导机会。将开设与项目目标紧密结合的新课程，包括关于使用图形处理器的并行编程以及关于科学数据可视化和管理的课程。项目小组成员致力于招募少数族裔学生。该项目的结果将作为研究论文和免费提供的工具在项目网站(http://www.cs.utah.edu/~csilva/projects/NSF-IIS-0751152/).上传播

Advanced computing capabilities are now essential to solve complex problems in science and engineering. Computer models have become fundamental to basic research. They are increasingly useful in addressing, in realistic detail, the subtle parameters of the physical systems being modeled. Underlying this increasing relevance of computer models is the enormous, and relatively recent, increase in available low-cost compute power. These advances in computing power and hence in computer modeling and simulation have brought about the emergent field of scientific computing, in which scientists and engineers from multiple disciplines collaborate in understanding a variety of complex systems not approachable only a few years ago.This infrastructure project establishes a high-resolution display wall to be used for scientific visualization at the Polytechnic University of New York and high-performance GPU-based computing cluster at the Scientific Computing and Imaging Institute (SCI Institute) at the University of Utah. This unique resource enables scientists to efficiently carry out increasingly complex scientific computations and visualizations in a collaborative environment. The infrastructure enables research in efficient execution of simulations; streamlining the creation of complex data products; producing high-quality visualizations; and scientific workflows leading to simplifying the process of designing simulations and analyzing their results. This project has the potential to impact a variety of applications where computation, visualization, and management of scientific data are currently the bottlenecks. Through our interdisciplinary collaborations, this project will have immediate impact in helping improve the scientific discovery process. The involvement of graduate and undergraduate students in the project will provide mentoring opportunities. New courses will be offered that are tightly integrated with the goals of the project, including courses on parallel programming using GPUs and on scientific data visualization and management. The project team members are committed to recruiting minority students.The results of this project will be disseminated as research papers and as freely available tools in the project website (http://www.cs.utah.edu/~csilva/projects/NSF-IIS-0751152/).