@inproceedings{6356a57bd94046c8adb8c5c22adbd690,
title = "A lightweight communication runtime for distributed graph analytics",
abstract = "Distributed-memory multi-core clusters enable in-memory processing of very large graphs with billions of nodes and edges. Recent distributed graph analytics systems have been built on top of MPI. However, communication in graph applications is very irregular, and each host exchanges different amounts of non-contiguous data with other hosts. MPI does not support such a communication pattern well, and it has limited ability to integrate communication with serialization, deserialization, and graph computation tasks. In this paper, we describe a lightweight communication runtime called LCI that supports a large number of threads on each host and avoids the semantic mismatches between the requirements of graph computations and the communication library in MPI. The implementation of LCI is informed by lessons learnt from two baseline MPI-based implementations. We have successfully integrated LCI with two state-of-The-Art graph analytics systems-Gemini and Abelian. LCI improves the latency up to 3.5x for microbenchmarks compared to MPI solutions and improves the end-To-end performance of distributed graph algorithms by up to 2x.",
keywords = "Clusters, Communication systems, Graph analytics",
author = "Dang, {Hoang Vu} and Roshan Dathathri and Gurbinder Gill and Alex Brooks and Nikoli Dryden and Andrew Lenharth and Loc Hoang and Keshav Pingali and Marc Snir",
note = "Funding Information: This research was supported by National Science Foundation (NSF) grant numbers 1337217, 1337281, 1406355, 1618425, 1725322 Publisher Copyright: {\textcopyright} 2018 IEEE.; 32nd IEEE International Parallel and Distributed Processing Symposium, IPDPS 2018 ; Conference date: 21-05-2018 Through 25-05-2018",
year = "2018",
month = aug,
day = "3",
doi = "10.1109/IPDPS.2018.00107",
language = "English (US)",
isbn = "9781538643686",
series = "Proceedings - 2018 IEEE 32nd International Parallel and Distributed Processing Symposium, IPDPS 2018",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "980--989",
booktitle = "Proceedings - 2018 IEEE 32nd International Parallel and Distributed Processing Symposium, IPDPS 2018",
address = "United States",
}