CSMqGraph: Coarse-Grained and Multi-external-storage Multi-queue I/O Management for Graph Computing

Abstract

As graphs continue growing, external storage graph processing systems serve as a promising alternative to distributed in-memory solutions for low cost and high scalability. To obtain high I/O throughput, these systems usually use multiple external storage devices. They adopt the operating system I/O management method based on striped volume, resulting in unsatisfactory performance, such as low sequential bandwidth utilization of each external storage device, limited I/O parallelism and expensive management overhead. In this paper, we analyzed the problems of the operating system I/O management method based on striped volume. Then we designed CSMqGraph, a graph processing system adopts coarse-grained striping method matching sequential large I/O to fully utilize the maximum sequential bandwidth of each external storage device and an I/O management strategy based on multi-external-storage multi-queue making I/O threads dedicated to each external storage device to further improve I/O throughput and fully exploit the parallelism of multiple external storage devices. For different graph algorithms and datasets, our evaluation shows that CSMqGraph consistently outperforms state-of-the-art engines GridGraph by up to 40%, and has better I/O scalability.