장명환/박정민/조익현/배덕호’s paper has been accepted in

Title: RealGraph+: A High-Performance Single-Machine-Based Graph Engine that Utilizes IO Bandwidth Effectively
Author: Myung-Hwan Jang, Jeong-Min Park, Ikhyeon Jo, Duck-Ho Bae, and Sang-Wook Kim
Abstract
This paper proposes RealGraph+, an improved version of RealGraph that processes large-scale real-world graphs efficiently in a single machine. Via a preliminary analysis, we observe that the original RealGraph does not fully utilize the IO bandwidth provided by NVMe SSDs, a state-of-the-art storage device. In order to increase the IO bandwidth, we equip RealGraph+ with three optimization strategies to issue more-frequent IO requests: (1) Userspace IO, (2) Asynchronous IO, and (3) SIMD processing. Via extensive experiments with four graph algorithms and six real-world datasets, we show that (1) each of our strategies is effective in increasing the IO bandwidth, thereby reducing the execution time; (2) RealGraph+ with all of our strategies improves the original RealGraph significantly; (3) RealGraph+ outperforms state-of-theart single-machine-based graph engines dramatically; (4) it shows performance comparable to or even better than those of other distributed-system-based graph engines.