Compile-Time Detection of False Sharing via Loop Cost Modeling

False sharing, which occurs when multiple threads access different data elements on the same cache line, and at least one of them updates the data, is a well known source of performance degradation on cache coherent parallel systems. The application developer is often unaware of this problem during program creation, and it can be hard to detect instances of its occurrence in a large code. In this paper, we present a compile-time cost model for estimating the performance impact of false sharing on parallel loops. Using this model, we are able to predict the amount of false sharing that could occur when the loop is executed, and can indicate the percentage of program execution time that is due to maintaining the coherence of data from false sharing. We evaluated our model by comparing its predictions obtained on several computational kernels using 2 to 48 threads against that from actual execution. The results showed that our model can accurately quantify the impact of false sharing on loop performance at compile-time.