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Library-Independent Data Race Detection

机译:与库无关的数据竞速检测

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摘要

Data races are a common problem on shared-memory parallel computers, including multicores. Analysis programs called race detectors help find and eliminate them. However, current race detectors are geared for specific concurrency libraries. When programmers use libraries unknown to a given detector, the detector becomes useless or requires extensive reprogramming. We introduce a new synchronization detection mechanism that is independent of concurrency libraries. It dynamically detects synchronization constructs based on a characteristic code pattern. The approach is non-intrusive and applicable to various concurrency libraries. Experimental results confirm that the approach identifies synchronizations and detects data races regardless of the concurrency libraries involved. With this mechanism, race detectors can be written once and need not be adapted to particular libraries.
机译:数据争用是共享内存并行计算机(包括多核)上的常见问题。称为种族探测器的分析程序可帮助查找和消除它们。但是,当前的竞争检测器适用于特定的并发库。当程序员使用给定检测器未知的库时,该检测器将变得无用或需要大量重新编程。我们引入了一种新的同步检测机制,该机制独立于并发库。它根据特征码模式动态检测同步结构。该方法是非侵入性的,适用于各种并发库。实验结果证实,该方法可以识别同步并检测数据竞争,而与所涉及的并发库无关。通过这种机制,种族检测器可以编写一次,而无需适应特定的库。

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