Library-Independent Data Race Detection

Abstract

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.