https://doi.org/10.1145/3392717.3392753

Vectorization seeks to accelerate computation through data-level parallelism. Vectorization has been applied to graph processing, where the graph is traversed either in a push style or a pull style. As it is not well understood which style will perform better, there is a need for both vectorized push and pull style traversals. This paper is the first to present a general solution to vectorizing push style traversal. It more-over presents an enhanced vectorized pull style traversal.

Our solution consists of three components: CleanCut, a graph partitioning approach that rules out inter-thread race conditions; VectorFast, a compact graph representation that supports fast-forwarding through the edge stream; and Graptor, a domain-specific language and compiler for auto-vectorizing and optimizing graph processing codes.

Experimental evaluation demonstrates average speedups of 2.72X over Ligra, 2.46X over GraphGrind, and 2.33X over GraphIt. Graptor outperforms Grazelle, which performs vectorized pull style graph processing, by 4.05 times.