@inproceedings{69b3b24b0d144d439399c0ea1fae50f7,
title = "HyGN: Hybrid Graph Engine for NUMA",
abstract = "Modern shared-memory platforms embrace the Non-uniform Memory Access (NUMA) architecture - they have physically distributed, yet cache-coherent shared-memory. This paper explores the feasibility of a shared-memory graph processing engine for NUMA platforms inspired by designs that target zero-sharing platforms. This work exploits the characteristics of two processing modes, synchronous and asynchronous, in the context of the shared-memory NUMA platform. Depending on the algorithm, phase of execution, and graph topology, synchronous and asynchronous modes hold unique advantages over one another. We then explore a hybrid solution that combines synchronous and asynchronous processing within the same graph computation task and harness optimizations therein. An extensive evaluation using graphs with billions of edges and empirical comparisons with several state-of-the-art solutions demonstrate the performance advantages of our design.",
author = "Tanuj Aasawat and Tahsin Reza and Kazuki Yoshizoe and Matei Ripeanu",
note = "Publisher Copyright: {\textcopyright} 2020 IEEE.; 8th IEEE International Conference on Big Data, Big Data 2020 ; Conference date: 10-12-2020 Through 13-12-2020",
year = "2020",
month = dec,
day = "10",
doi = "10.1109/BigData50022.2020.9378430",
language = "English",
series = "Proceedings - 2020 IEEE International Conference on Big Data, Big Data 2020",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "383--390",
editor = "Xintao Wu and Chris Jermaine and Li Xiong and Hu, {Xiaohua Tony} and Olivera Kotevska and Siyuan Lu and Weijia Xu and Srinivas Aluru and Chengxiang Zhai and Eyhab Al-Masri and Zhiyuan Chen and Jeff Saltz",
booktitle = "Proceedings - 2020 IEEE International Conference on Big Data, Big Data 2020",
address = "United States",
}