In Situ Processing and Visualization for Peta- and Exa-Scale Simulations

Peta 级和 Exa 级模拟的原位处理和可视化

• 批准号: 0850566
• 负责人: Kwan-Liu Ma
• 金额: $ 42.5万
• 依托单位: University of California-Davis
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2009
• 资助国家: 美国
• 起止时间: 2009-07-01 至 2013-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0850566&HistoricalAwards=false
• 关键词: Situ; Processing; Visualization; Peta; Exa

"This award is funded under the American Recovery and Reinvestment Act of 2009 (Public Law 111-5)."The proposed research will realize in-situ visualization at extreme scale, and deliver a feasible data-understanding solution to scientists whose work will rely on extreme-scale supercomputing, such as those in the NSF PetaApps program. To make the in-situ approach feasible, project will have to either transform existing visualization algorithms or develop a set of new algorithms. These algorithms must be not only scalable but also low cost. The proposed work will build on the PI?s prior success and on-going effort in developing visualization algorithms and systems, as well as his long track record of successful collaboration with application scientists in a variety of areas. The PI directs the Institute for Ultrascale Visualization, a 5-year project funded by the DOE SciDAC program to address the data visualization challenges of petascale computing. The proposed project will be able to leverage, in particular, the Institute?s research in scalable parallel visualization and I/O. This leverage is crucial since it allows this project to focus on application requirements, hardware capabilities/limitations, integration, evaluation, and coupling with the simulation. Broader Impact: The key impact anticipates is to achieve is the demonstration of a working and attractive solution for scientists to possibly comprehend the vast amounts of data generated by petacale computing.PI's won?t have to store petascale data for validating, verifying, and analyzing petascale simulations. This project will provide training for graduate students in the area of computational science and high-performance computing. The new algorithms and software tools developed in the project will be disseminated through the annual visualization workshops and tutorials that the PI has been offering to both the supercomputing and visualization communities.

“该奖项是根据2009年美国复苏和再投资法案（公法111-5）资助的。“拟议中的研究将实现极端规模的原位可视化，并为科学家提供可行的数据理解解决方案，这些科学家的工作将依赖于极端规模的超级计算，例如NSF PetaApps计划。为了使原位方法可行，项目将不得不改变现有的可视化算法或开发一套新的算法。这些算法不仅必须是可扩展的，而且成本低。拟议的工作将建立在PI？他在开发可视化算法和系统方面的成功和持续努力，以及他与各个领域的应用科学家成功合作的长期记录。PI指导超尺度可视化研究所，这是一个由DOE SciDAC计划资助的为期5年的项目，旨在解决千万亿次计算的数据可视化挑战。拟议项目将能够特别利用研究所？在可扩展并行可视化和I/O方面的研究。这种利用是至关重要的，因为它允许这个项目专注于应用程序的要求，硬件功能/限制，集成，评估，并与模拟耦合。更广泛的影响：预期的关键影响是实现的是一个工作和有吸引力的解决方案，为科学家可能理解的大量数据产生的petacale计算示范。不必存储千万亿次数据来验证、检验和分析千万亿次模拟。 该项目将为计算科学和高性能计算领域的研究生提供培训。该项目中开发的新算法和软件工具将通过PI向超级计算和可视化社区提供的年度可视化研讨会和教程进行传播。