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。它们在处理现实细节中越来越有用，被建模的物理系统的微妙参数。计算机模型的这种日益增长的相关性的基础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仿真的这些进步带来了科学计算的新兴领域，该基础设施项目建议在科学计算和成像研究所建立一个基于GPU的高性能计算集群，（SCI研究所）在犹他州的大学。与使用CPU进行计算和GPU进行图形和可视化任务的标准方法相反，该项目旨在探索GPU用于一般计算的能力。我们的目标是获得比目前基于CPU的计算集群更高的每个节点性能。每个节点有多个GPU，这种独特的计算资源使科学家能够有效地进行日益复杂的科学计算。拟议的基础设施还包括一个用于可视化的高分辨率显示墙、数据库和Web服务器。该基础设施可实现高效执行模拟的研究;简化复杂数据产品的创建;生成高质量的可视化;以及简化设计模拟和分析结果的过程的科学工作流程。该项目有可能影响各种应用程序，其中科学数据的计算，可视化和管理是目前的瓶颈。通过我们的跨学科合作，该项目将在帮助改善科学发现过程中产生直接影响。研究生和本科生参与该项目将提供指导机会。将提供与项目目标紧密结合的新课程，包括使用GPU并行编程和科学数据管理课程。该项目的结果将作为研究论文和项目网站（http：//www.cs.utah.edu/jujucsilva/projects/NSF-IIS-0751152/）上免费提供的工具予以传播。

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 proposes the establishment of a high-performance GPU-based computing cluster at the Scientific Computing and Imaging Institute (SCI Institute) at the University of Utah. In contrast to the standard approach of using CPUs for computation and GPUs for graphics and visualization tasks, this project aims to explore the power of GPUs for general computations. Our goal is to obtain substantially higher performance per node than what can currently be accomplished with a CPU-based computing cluster. With multiple GPUs per node, this unique computational resource enables scientists to efficiently carry out increasingly complex scientific computations. The proposed infrastructure also includes a high-resolution display wall to be used for visualization, and database and Web servers.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 management. The PIs 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/).