SHF: SMALL: Ant: Automatic and Manual Debugging Support for Massively Parallel Programs

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。该奖项资助的研究目标是如何调试在大型并行系统上运行的程序这一难题。形成单个计算的成百上千个并行任务的状态对于程序员来说过于复杂，无法有效地分析。该项目将开发工具来查找不同进程状态之间的相似性，从而简化程序员的任务。找到这些相似任务的挑战在于如何高效地完成任务，同时又不会造成过高的开销，导致工具无法使用。幼稚的实现会将所有处理器的状态相互比较，并且会引入开销随着处理器数量的平方而增加。我们的方法将依次细化类似过程的集合，将使用程序行为的关键属性（例如通信模式）来执行这种分组。我们还将研究使用这些相似的过程组，以允许为顺序程序开发的不变性和基于统计的技术（如值和PC不变性）有效地适应并行程序。因为这些技术寻找很少发生的程序活动，所以将它们一起应用于不同的过程将会在分析中引入噪声，严重地降低了它们的准确性。使用我们的分组策略将允许这些技术的有效并行化，使它们能够以比使用顺序应用程序时更少的开销来应用。

This award is funded under the American Recovery and Reinvestment Act of 2009 (Public Law 111-5). The research funded by this award targets the difficult problem of how to debug programs running on large parallel systems. The state of hundreds to hundreds of thousands of parallel tasks that form a single computation are too complicated for a programmer to usefully analyze. This project will develop tools to find similarities between the state of different processes, simplifying the task of the programmer. The challenge in finding these similar tasks is to do it efficiently, without imposing anoverhead so hight that the tool is useless. A naive implementation would compare the state of all processors against one another, and would introduce overheads increasing as the square of the number of processors. Our approach will successively refine sets of similar processes, will use key attributes of program behavior (e.g. communication patterns) to perform this grouping. We will also investigate the use these groups of similar processes to allow invariance and statistically based techniques developed for sequential programs (such as value and PC invariance) to be effectively adapted to parallel programs. Because these techniques look for rarely occurring programactivities, applying them to disparate processes together will introducenoise into the analysis, severely diminishing their accuracy. The use of our grouping strategy will allow effective parallelization of the techniques, allowing them to be applied with significantly less overhead than when used with sequential applications.