Analysis of Randomized Work Stealing with False Sharing

This paper analyzes the overhead due to false sharing when parallel tasks are scheduled using randomized work stealing (RWS). We obtain high-probability bounds on the cache miss overhead, including the overhead due to false sharing, for several parallel cache-efficient algorithms when scheduled using RWS. These include algorithms for fundamental problems, such as matrix computations, FFT, sorting, basic dynamic programming, list ranking and graph connected components. Our main technical contribution, from which these results follow, is the derivation of nontrivial high-probability bounds on the number of steals incurred by these algorithms in the presence of false sharing, when using RWS.