@inproceedings{e18e88c7021e4745b065873282ab37f5,
title = "VC-Tune: Tuning and Exploring Distributed Vertex-Centric Graph Systems",
abstract = "Distributed vertex-centric graph systems, or VC-systems, have achieved tremendous success in the industry. A common usage pattern of VC-systems is multi-processing, or the concurrent processing of multiple unit tasks. Example multi-processing includes answering multiple single-source shortest path queries on a graph. However, concurrent processing of all the unit tasks may overload the system with excessive memory usage, leading to intolerable system delays. To ad-dress the important challenge, we present V C- Tune, a system with a convenient interface to help practitioners orchestrate the unit tasks for improving the overall performance within the system limit. This demonstration allows the audience to interact with our system to explore the configuration space of multi-processing in VC-systems and compare different sys-tem configurations. In addition, we embed into the system an automatic configuration search algorithm, which can directly recommend to the practitioners a suitable configuration that gives a satisfactory system performance. An introduction video is at (https://sites.google.com/view/vc-tune-video).",
keywords = "Distributed Systems, Graph Processing",
author = "Zichen Zhu and Siqiang Luo and Xiaokui Xiao and Yin Yang and Dingheng Mo and Yufei Han",
note = "Publisher Copyright: {\textcopyright} 2022 IEEE.; 38th IEEE International Conference on Data Engineering, ICDE 2022 ; Conference date: 09-05-2022 Through 12-05-2022",
year = "2022",
doi = "10.1109/ICDE53745.2022.00283",
language = "English",
series = "Proceedings - International Conference on Data Engineering",
publisher = "IEEE Computer Society",
pages = "3142--3145",
booktitle = "Proceedings - 2022 IEEE 38th International Conference on Data Engineering, ICDE 2022",
address = "United States",
}