TriX: Triangle counting at extreme scale

Abstract

Triangle counting is widely used in many applications including spam detection, link recommendation, and social network analysis. The DARPA Graph Challenge seeks a scalable solution for triangle counting on big graphs. In this paper we present TriX, a scalable triangle counting framework, which is comprised of a 2-D graph partition strategy and a binary search based intersection algorithm designed for GPUs. The 2-D partition provides balanced work division among multiple GPUs. On the other hand, binary search based intersection achieves fine-grained parallelism on GPUs via intra-warp scheduling and coalesced memory access. TriX is able to scale to a large number of GPUs, and count triangles on billion-node graph (2 billion node, 64 billion edges) within 35 minutes, achieving over 16 million traverse edges per second (TEPS).