SHF: Small: Interleaving Constrained Parallel Runtime System for Tolerating Concurrency Bugs

未来的处理器芯片预计将拥有数百甚至数千个处理器核心。为了利用这种巨大的计算能力，程序员需要将他们的应用程序并行化。然而，并行编程是出了名的困难。今天使用的几乎所有生产并发软件系统都包含耗资数十亿美元的错误。为了应对这一挑战，本研究正在开发并行运行时机制，使即使是有缺陷的软件也可以在生产系统中正确运行。当前并行编程模型的基本问题是，它们向并行运行时系统暴露了无限数量的线程交织，并且生产系统中的大多数交织仍然未经测试。这项研究正在探索两个方向，以避免错误的交错在生产运行中表现出来。第一种方法使用基于采样的低开销数据竞争检测器来检测错误交织，然后避免错误交织。第二种方法将生产运行线程交错限制在一组经过测试的交错中，这可以针对大多数类型的并发错误提供全面的免疫力。作为这项研究的一部分开发的软件工具将帮助软件开发人员和研究人员。学生还将在他们的课程项目中使用这些生产力工具。

Future processor chips are expected to have hundreds or even thousands of processor cores. To take advantage of this massive computing power, programmers need to parallelize their applications. Parallel programming, however, is notoriously difficult. Almost all the production concurrent software systems used today contain bugs costing billions of dollars. To address this challenge, this research is developing parallel runtime mechanisms that could make it possible for even buggy software to run correctly in a production system.The fundamental problem with the current parallel programming models is that they expose an unbounded number of thread interleavings to the parallel runtime system, and a majority of the interleavings in a production system remain untested. This research is exploring two directions to avoid incorrect interleavings from manifesting in a production run. The first approach uses a sampling-based low overhead data race detector for detecting incorrect interleavings, which are then avoided. The second approach constrains production run thread interleavings to a set of tested interleavings, which could provide comprehensive immunity against most types of concurrency bugs. Software tools developed as part of this research will help software developers and researchers. Students will also use these productivity tools in their course projects.