T-Rex: a dynamic race detection tool for C/C++ transactional memory applications

Abstract

Transactional memory (TM) has reached a maturity level and programmers have started using this programming model to parallelize their applications. However, although much effort has been put into the development of TM systems, there is still lack of debugging and development tools for TM applications, such as race detection tools. Previous definitions of transactional data race often impose constraints on the TM implementation or the programming language and cannot be widely applied to current STM designs. We propose a new definition of transactional data race that follows the programmer's intuition of racy accesses, is independent of thread interleaving, can accommodate popular STM systems, and allows common programming idioms. Based on this definition, we design and implement T-Rex, a precise dynamic race detection tool for C/C++ TM programs. Using T-Rex we discover transactional data races in STAMP applications that, to the best of our knowledge, have not been previously reported. Our experiments also show that T-Rex runtime overhead is comparable to state-of-the-art lock-based race detection tools, despite the extra work required to handle transactional memory semantics.