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

多核处理器无处不在，从服务器到手机，都需要类似的多线程程序来利用多核。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的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空间。当程序在不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空间为多线程程序提供了强大的安全属性。虽然存在数据竞争检测技术，但它们的执行速度太慢，无法实现始终在线的数据竞争检测。为了使数据竞争检测变得实用，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。研究包括通过形式证明、多线程基准测试套件的实验和详细的硬件模拟来验证这些技术。研究人员计划公开分发为该项目建立的系统，以方便其他研究人员的审查，并将研究成果整合到他们教授的计算机体系结构资源中。如果成功，这项拟议的技术将提高在今天和未来的S多核设备上运行的海量多线程代码的安全性和质量。

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.