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Many programs exploit shared-memory parallelism using multithreading. Threaded codes typically use locks to coordinate access to shared data. In many cases, contention for locks reduces parallel efficiency and hurts scalability. Being able to quantify and attribute lock contention is important for understanding where a multithreaded program needs improvement. This paper proposes and evaluates three strategies for gaining insight into performance losses due to lock contention. First, the authors consider using a straightforward strategy based on call stack profiling to attribute idle time and show that it fails to yield insight into lock contention. Second, they consider an approach that builds on a strategy previously used for analyzing idleness in work-stealing computations; they show that this strategy does not yield insight into lock contention.
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