FAST-CON: a Multi-source Approach for Efficient S- T Connectivity on Sparse Graphs

S-t connectivity is a decision problem asking, for vertices s and $t$ in a graph, if $t$ is reachable from s. Many parallel solutions for GPUs have been proposed in literature to solve the problem. The most efficient, which rely on two concurrent BFS starting from s and $t$ have shown limitations when applied on sparse graphs (i.e., graphs with low average degree). In this paper we present FAST-CON, an alternative solution based on multi-source BFS and adjacency matrix to better exploit the massive parallelism of the GPU architectures with any type of graph. The results show that FAST-CON achieves speedup up to one order of magnitude for dense graphs and up to two orders of magnitude for sparse graphs compared to the state of the art solutions.