XPS: CLCCA: Improving Parallel Program Reliability Through Novel Approaches to Precise Dynamic Data Race Detection

从服务器到智能手机，多核处理器无处不在，这就要求多核程序也同样流行，以利用多核的优势。不幸的是，编写多线程代码仍然处于容易出错的手动同步、未经检查的并发错误和未定义语义的狂野西部时代。多线程程序中错误的一个常见症状是数据区。当一个程序在没有同步的情况下对某个位置执行并发更新时，就会出现数据竞争。在程序执行过程中自动检测数据字符可以增强多线程程序的安全性。虽然存在数据竞争检测技术，但它们会使程序执行速度变慢，无法实现始终在线的强制执行。为了使始终在线的数据竞争检测切实可行，该项目旨在开发新的算法、语言扩展、运行时系统和硬件支持，以提高数据竞争检测的效率。该研究包括验证这些技术通过正式的证明，实验与多线程基准套件，并详细的硬件仿真。研究人员计划公开发布为该项目构建的系统，以方便其他研究人员进行检查，并将研究结果整合到他们教授的计算机体系结构课程中。如果成功的话，这项技术将提高现在和将来运行在计算机上的大量多线程代码的安全性和质量。的多核设备。

The ubiquity of multi-core processors in everything from servers tosmartphones has demanded a similar prevalence of multi-threadedprograms to take advantage of multiple cores. Unfortunately, writingmulti-threaded code is still in the Wild West era of error-prone manualsynchronization, unchecked concurrency bugs, and undefined semantics.One common symptom of an error in a multi-threaded program is a datarace. Data races arise when a program performs concurrent updates tosome location without synchronization. Automatically detecting dataraces during program execution enforces strong safety properties formulti-threaded programs. While techniques for data race detection existthey slow program execution too much to be viable for always-onenforcement.To make always-on detection of data races practical, the project aimsto develop new algorithms, language extensions, runtime systems, andhardware support to improve the efficiency of data race detection. Theresearch includes validation of these techniques via formal proofs,experiments with multi-threaded benchmark suites, and detailed hardwaresimulation. The researchers plan to openly distribute the systemsbuilt for this project to facilitate examination by other researchersand integrate the research results into the computer architecturecourses they teach. If successful, the proposed technology willimprove the safety and quality of the vast amounts of multi-threadedcode running on today's and tomorrow?s multi-core devices.