π€ AI Summary
This paper addresses the high computational complexity of parallel algorithms for single-source reachability and shortest paths on directed graphs. We propose a generic black-box framework that applies a shallow graph transformation to convert any input graph into an equivalent, structurally simpler, and shallower graphβenabling existing shortcut- and hopset-based parallel algorithms to run directly and efficiently on the transformed instance. Crucially, our framework decouples shortcut and hopset construction while weakening structural assumptions previously required on the original graph. Leveraging near-linear-work parallel graph primitives, our approach significantly simplifies the design and analysis of multiple classical algorithms, enhancing both theoretical interpretability and practical implementability. The framework is model-agnostic, supporting diverse parallel computing models including PRAM and MPC.
π Abstract
We introduce a blackbox framework that simplifies all known parallel algorithms with near-linear work for single-source reachability and shortest paths in directed graphs. Specifically, existing reachability algorithms rely on constructing shortcuts; our blackbox allows these algorithms that construct shortcuts with hopbound $h$ to assume the input graph $G$ is ``shallow'', meaning if vertex $s$ can reach vertex $t$, it can do so in approximately $h$ hops. This assumption significantly simplifies shortcut construction [Fin18, JLS19], resulting in simpler parallel reachability algorithms. Furthermore, our blackbox extends naturally to simplify parallel algorithms for constructing hopsets and, consequently, for computing shortest paths [CFR20 , CF23 , RHM+23 ].