11 citations · 28 across the 7 of their papers we have counts for
7 papers
Parallel Contraction Hierarchies Can Be Efficient and Scalable
Zijin Wan, Xiaojun Dong, Letong Wang +3
Contraction Hierarchies (CH) (Geisberger et al., 2008) is one of the most widely used algorithms for shortest-path queries on road networks. Compared to Dijkstra's algorithm, CH en…
Parallel Cluster-BFS and Applications to Shortest Paths
Letong Wang, Guy Blelloch, Yan Gu +1
Breadth-first Search (BFS) is one of the most important graph processing subroutines, especially for computing the unweighted distance. Many applications may require running BFS fr…
PASGAL: Parallel And Scalable Graph Algorithm Library
Xiaojun Dong, Yan Gu, Yihan Sun +1
In this paper, we introduce PASGAL (Parallel And Scalable Graph Algorithm Library), a parallel graph library that scales to a variety of graph types, many processors, and large gra…
Fast and Space-Efficient Parallel Algorithms for Influence Maximization
Letong Wang, Xiangyun Ding, Yan Gu +1
Influence Maximization (IM) is a crucial problem in data science. The goal is to find a fixed-size set of highly-influential seed vertices on a network to maximize the influence sp…
Parallel Strong Connectivity Based on Faster Reachability
Letong Wang, Xiaojun Dong, Yan Gu +1
Computing strongly connected components (SCC) is a fundamental problems in graph processing. As today's real-world graphs are getting larger and larger, parallel SCC is increasingl…
Provably Fast and Space-Efficient Parallel Biconnectivity
Xiaojun Dong, Letong Wang, Yan Gu +1
Biconnectivity is one of the most fundamental graph problems. The canonical parallel biconnectivity algorithm is the Tarjan-Vishkin algorithm, which has optimal work (numb…
Maximal Information Propagation with Budgets
Haomin Shi, Yao Zhang, Zilin Si +2
In this paper, we present an information propagation game on a network where the information is originated from a sponsor who is willing to pay a fixed total budget to the players…