Designing a spacecraft, or any other complex engineering system, requires extensive simulation and analysis work. Oftentimes, the large amounts of simulation data generated are very difficult and time consuming to analyze, with the added risk of overlooking potentially critical problems in the design. The authors have developed a generic data analysis tool that can quickly sort through large data sets and point an analyst to the areas in the data set that cause specific types of failures. The first version of this tool was a serial code and the current version is a parallel code, which has greatly increased the analysis capabilities. This paper describes the new implementation of this analysis tool on a graphical processing unit, and presents analysis results for NASA's Orion Monte Carlo data to demonstrate its capabilities.
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机译：设计航天器或任何其他复杂的工程系统，需要进行大量的模拟和分析工作。通常，生成大量的仿真数据非常困难且耗时，而且存在忽略设计中潜在关键问题的风险。作者开发了一种通用的数据分析工具，该工具可以快速对大型数据集进行排序，并将分析师指向数据集中导致特定类型故障的区域。该工具的第一个版本是一个串行代码，而当前版本是一个并行代码，这大大提高了分析能力。本文介绍了此分析工具在图形处理单元上的新实现，并提供了NASA Orion Monte Carlo数据的分析结果，以证明其功能。
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