Redio: Accelerating Disk-Based Graph Processing by Reducing Disk I/Os

Abstract

Disk-based graph systems store part or all of graph data on external devices like hard drives or SSDs, achieving scalability without excessive hardware. However, massive expensive disk I/Os remain the major performance bottleneck of disk-based graph processing. In this paper, we propose Redio, a new approach to accelerating disk-based graph processing by reducing disk I/Os. First, Redio observes that it is feasible to accommodate all vertex states in main memory and this can eliminate almost all vertex-related disk I/Os. Second, Redio introduces a dynamic selective scheduling scheme to identify inactive edges in each iteration and skip them when and only when such skipping can bring performance benefit. To improve its effectiveness, Redioin corporates a compact edge storage to improve data locality and an indexed bitmap to minimize its memory and computation overheads. We have implemented a single-node prototype for Redio under the edge-centric computation model. Extensive experiments show that Redio consistently outperforms well-known edge-centric disk-based systems in all experiments, delivering an average speedup of $4.33\times$ on HDDs and $5.33\times$ on SSDs over the fastest among them (i.e., GridGraph). Experimental results also show that Redio delivers an average speedup of $3.13\times$ on HDDs and $1.28\times$ on SSDs over the fastest among representative vertex-centric disk-based systems (i.e., FlashGraph).