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Redio: Accelerating Disk-Based Graph Processing by Reducing Disk I/Os
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DOI：10.1109/TC.2018.2875458.png)
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Abstract
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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 4.33x on HDDs and 5.33x on SSDs over the fastest among them (i.e., GridGraph). Experimental results also show that Redio delivers an average speedup of 3.13x on HDDs and 1.28x on SSDs over the fastest among representative vertex-centric disk-based systems (i.e., FlashGraph).
Keywords:
Disk I/O
edge-centric
graph processing
large graph
vertex-centric
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