Overview
In a multi-threaded execution, threads may negatively interfere when their private data contends for shared cache or positively interact when the data brought in by one thread is used by other threads. This paper presents a model of such cache behavior to predict locality without exhaustive simulation and provide insight into trends. The new model extends prior work that assumes no data sharing and uniform thread interleaving. Based on a single pass over an interleaved execution trace, one computes a set of per-thread statistics that includes the effect of thread interleaving and data sharing. The per-thread statistics is then composed to predict performance for all cache sizes, either for sub-clusters of threads or for futuristic environments with a larger number of similar threads.
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