Accelerating Precise Race Detection Using Commercially- Available Hardware Transactional Memory Support
Hassan Salehe Matar, Ismail Kuru, Serdar Taşiran, Roman Dementiev · 2014
It is typical for state-of-the-art dynamic race detection algorithms for C programs to slow down an application by a large factor. Our measurements indicate that a significant portion of this slowdown is due to additional lock-based synchronization performed by instrumentation code. This synchronization is necessary to ensure atomic update of analysis state. We present the first precise race detection tool that improves race-detection slowdown by using commercial hardware transactional memory support to synchronize analysis and program data. By careful choice of transaction sizes, we obtain noteworthy speedups over lock-based protection of race analysis metadata.