Raman, RaghavanZhao, JishengSarkar, VivekVechev, MartinYahav , Eran2017-08-022017-08-022012-07-06Raman, Raghavan, Zhao, Jisheng, Sarkar, Vivek, et al.. "Scalable and Precise Dynamic Datarace Detection for Structured Parallelism." (2012) https://hdl.handle.net/1911/96401.https://hdl.handle.net/1911/96401Existing dynamic race detectors suffer from at least one of the following three limitations: i) space overhead per memory location grows linearly with the number of parallel threads [13], severely limiting the parallelism that the algorithm can handle. (ii) sequentialization: the parallel program must be processed in a sequential order, usually depth-first [12, 24]. This prevents the analysis from scaling with available hardware parallelism, inherently limiting its performance. (iii) inefficiency: even though race detectors with good theoretical complexity exist, they do not admit efficient implementations and are unsuitable for practical use [4, 18]. We present a new precise dynamic race detector that leverages structured parallelism in order to address these limitations. Our algorithm requires constant space per memory location, works in parallel, and is efficient in practice. We implemented and evaluated our algorithm on a set of 15 benchmarks. Our experimental results indicate an average (geometric mean) slowdown of 2.78× on a 16core SMP system.14 ppengYou are granted permission for the noncommercial reproduction, distribution, display, and performance of this technical report in any format, but this permission is only for a period of forty-five (45) days from the most recent time that you verified that this technical report is still available from the Computer Science Department of Rice University under terms that include this permission. All other rights are reserved by the author(s).Technical reportTR12-01