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Statistical assertion: A more powerful method for debugging scientific applications

机译:统计断言:调试科学应用程序的更强大方法

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Traditional debuggers are of limited value for modern scientific codes that manipulate large complex data structures. Current parallel machines make this even more complicated, because the data structure may be distributed across processors, making it difficult to view/interpret and validate its contents. Therefore, many applications' developers resort to placing validation code directly in the source program. This paper discusses a novel debug-time assertion, called a "Statistical Assertion", that allows using extracted statistics instead of raw data to reason about large data structures, therefore help locating coding defects. In this paper, we present the design and implementation of an 'extendable' statistical-framework which executes the assertion in parallel by exploiting the underlying parallel system. We illustrate the debugging technique with a molecular dynamics simulation. The performance is evaluated on a 20,000 processor Cray XE6 to show that it is useful for real-time debugging.
机译:对于调试大型复杂数据结构的现代科学代码,传统调试器的价值有限。当前的并行机使这一点变得更加复杂,因为数据结构可能分布在处理器之间,从而难以查看/解释和验证其内容。因此,许多应用程序的开发人员都将验证代码直接放在源程序中。本文讨论了一种称为“统计断言”的新颖调试时断言,该断言允许使用提取的统计信息而不是原始数据来推理大型数据结构,从而帮助定位编码缺陷。在本文中,我们介绍了“可扩展”统计框架的设计和实现,该框架通过利用底层并行系统并行执行断言。我们通过分子动力学仿真说明了调试技术。在20,000个处理器Cray XE6上对性能进行了评估,表明该性能对于实时调试很有用。

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