Parallel algorithm

Work-Optimal Parallel Minimum Cuts for Non-Sparse Graphs

We present the first work-optimal polylogarithmic-depth parallel algorithm for the minimum cut problem on non-sparse graphs. For mn1+ϵ for any constant ϵ>0, our algorithm requires O(mlogn) work and O(log3n) depth and succeeds with high probability. Its work matches the best O(mlogn) runtime for sequential algorithms [MN STOC’20; GMW SOSA’21]. This improves the previous best work by Geissmann and Gianinazzi [SPAA’18] by O(log3n) factor, while matching the depth of their algorithm.