SCoReViS: Scalable Collaborative and Remote Visualization Software

SCoReViS：可扩展的协作和远程可视化软件

• 批准号: 0751397
• 负责人: Kelly Gaither
• 金额: $ 88.07万
• 依托单位: University of Texas at Austin
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2008
• 资助国家: 美国
• 起止时间: 2008-03-01 至 2013-02-28
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0751397&HistoricalAwards=false
• 关键词: SCoReViS; Scalable; Collaborative; Remote; Visualization

SCoReViS: Scalable Collaborative and Remote Visualization SoftwarePI: Kelly Gaither, University of Texas at AustinThis project addresses what is fast becoming the most common, most severe bottleneck in high-end computational science: the inability of users to analyze their data in real time because of the limitations of their local systems and limited network bandwidth that cannot support transfer of tremendous data sets. The project will bring data analysis and visualization capability in line with HPC modeling and simulation capability to enable new kinds of interaction, increasing the likelihood of discovery. The Challenge: Scientific visualization is a fundamental data analysis technique for simulation-based research. Through 2-D and 3-D images, scientific visualization helps scientists explore, make sense of, and communicate data, whether it is modeling a hurricane, tracing the arterial blood flow of a heart, or exploring a super massive black hole. However, high performance computing (HPC) systems capabilities are racing far ahead of users' ability to effectively visualize the data they produce. As petaflop systems produce simulation output of unprecedented scale, it is becoming unfeasible to move these enormous data sets over networks to visualization systems and to use special-purpose visualization systems to interact with them. To fully achieve the scientific impact of these costly tera-and petascale systems, we need to improve the visualization capabilities for high end users. As with HPC, this requires scalable visualization tools that aggregate the capabilities of many compute nodes, while rendering the data close to the source to eliminate costly network transfers. This requires remote visualization interfaces to these large-scale visualization systems, enabling remote users to work interactively with their data.The Solution: The development of the Scalable Collaborative and Remote Visualization Software (SCoReViS) is a direct response to the need for next-generation visualization tools for large-scale HPC platforms and dedicated graphics clusters. SCoReViS will:o Leverage the computational power of tera- and petascale HPC and large GPU-based graphics clusters, and scale seamlessly from the largest available platforms down to smaller systems deployed at scientists' local institutions;o Maximize the investments in large-scale systems by providing remote and collaborative access to visualization tools, making them available and effective for any researcher with a reasonably high-bandwidth network connection (e.g. consumer broadband service); o Provide general purpose visualization capabilities by supporting any software based on the standard OpenGL API, thus enabling most popular visualization applications; ando Create a platform of tools for scientists who compute at the largest scale and to promote the development of tools to address issues associated with large, time-dependent data sets. The key components will be assembled, optimized, packaged and supported to provide high performance, scalable remote/collaborative visualization on petascale HPC and graphics clusters.Impact: The potential impact of this project is immeasurable. The resulting software will be made available via open source licensing, enabling use by anyone with access to the TeraGrid, including diverse scientific disciplines. The remote and collaborative visualization capabilities enabled by SCoReViS will allow access by a broader community of researchers, increasing the ability of high performance computing (HPC) to address the largest problems facing us.

SCoReViS：可扩展的协作和远程可视化软件PI：Kelly Gaither，德克萨斯大学奥斯汀分校该项目解决了高端计算科学中最常见、最严重的瓶颈：由于本地系统的限制和有限的网络带宽无法支持传输大量数据集，用户无法真实的时间分析数据。该项目将使数据分析和可视化功能与HPC建模和仿真功能保持一致，以实现新型交互，增加发现的可能性。挑战：科学可视化是基于模拟的研究的基本数据分析技术。通过2D和3D图像，科学可视化可以帮助科学家探索、理解和交流数据，无论是建模飓风、追踪心脏的动脉血流还是探索超大质量黑洞。 然而，高性能计算（HPC）系统的能力远远领先于用户有效地可视化其产生的数据的能力。由于petaflop系统产生的仿真输出规模空前，将这些庞大的数据集通过网络移动到可视化系统并使用专用可视化系统与它们交互变得不可行。为了充分实现这些昂贵的万亿级和千万亿级系统的科学影响，我们需要提高高端用户的可视化功能。与HPC一样，这需要可扩展的可视化工具，这些工具可以聚合许多计算节点的功能，同时将数据呈现在靠近源的位置，以消除昂贵的网络传输。这就需要为这些大规模可视化系统提供远程可视化接口，使远程用户能够交互地处理他们的数据。解决方案：可扩展的协作和远程可视化软件（SCoReViS）的开发直接响应了大规模HPC平台和专用图形集群对下一代可视化工具的需求。SCoReViS将：o利用万亿次和千万亿次HPC以及基于GPU的大型图形集群的计算能力，并从最大的可用平台无缝扩展到科学家当地机构部署的较小系统;o通过提供对可视化工具的远程和协作访问，使其对任何具有合理高带宽网络连接的研究人员都可用并有效，从而最大限度地提高对大型系统的投资o透过支援任何以标准OpenGL API为基础的软件，提供通用的视觉化功能，从而使最流行的视觉化应用程式得以应用;为进行大规模计算的科学家创建一个工具平台，并促进工具的开发，以解决与大型、时间依赖性数据集相关的问题。关键组件将被组装、优化、打包和支持，以在千万亿次HPC和图形集群上提供高性能、可扩展的远程/协作可视化。影响：该项目的潜在影响不可估量。由此产生的软件将通过开源许可提供，使任何人都可以使用TeraGrid，包括不同的科学学科。SCoReViS支持的远程和协作可视化功能将允许更广泛的研究人员社区访问，提高高性能计算（HPC）解决我们面临的最大问题的能力。