ABi-BFS: A High-performance Parallel Breadth-First Search on Shared-memory Systems.

Breadth-first search (BFS) is a cornerstone in graph traversal, widely employed in areas such as social network analysis, routing algorithms, and biological network exploration. As the size of these graphs increases, the performance of BFS becomes significant. There are two key factors that influence BFS performance: synchronization overhead and memory access efficiency. To address them, we propose the ABi-BFS, an asynchronous and bidirectional optimized breadth-first search algorithm. ABi-BFS novelly designs an asynchronous mode for node-expanding and task-assignment processes to decrease the synchronization overhead and introduces an optimized strategy to select the frontier nodes in the bottom-up step of bidirectional search to lower the number of node accesses. Our experiment demonstrates that ABi-BFS outperforms other implementations of state-of-the-art PBFS algorithms on various graphs and achieves the highest scalability among them on shared-memory systems.