Accelerating dynamic data race detection using static thread interference analysis
- Publisher:
- ACM
- Publication Type:
- Conference Proceeding
- Citation:
- Proceedings of the 7th International Workshop on Programming Models and Applications for Multicores and Manycores, PMAM 2016, 2016, pp. 30-39
- Issue Date:
- 2016-03-12
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Copyright © 2016 ACM. Precise dynamic race detectors report an error if and only if more than one thread concurrently exhibits conict on a memory access. They insert instrumentations at compiletime to perform runtime checks on all memory accesses to ensure that all races are captured and no spurious warnings are generated. However, a dynamic race check for a particular memory access statement is guaranteed to be redundant if the statement can be statically identified as thread interference-free. Despite significant recent advances in dynamic detection techniques, the redundant check remains a critical factor that leads to prohibitive overhead of dynamic race detection for multithreaded programs. In this paper, we present a new framework that eliminates redundant race check and boosts the dynamic race detection by performing static optimizations on top of a series of thread interference analysis phases. Our framework is implemented on top of LLVM 3.5.0 and evaluated with an industry dynamic race detector TSAN which is available as a part of LLVM tool chain. 11 benchmarks from SPLASH2 are used to evaluate the effectiveness of our approach in accelerating TSAN by eliminating redundant interference-free checks. The experimental result demonstrates our new approach achieves from 1.4x to 4.0x (2.4x on average) speedup over original TSAN under 4 threads setting, and achieves from 1.3x to 4.6x (2.6x on average) speedup under 16 threads setting.
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