A lightweight communication runtime for distributed graph analytics

Hoang Vu Dang, Roshan Dathathri, Gurbinder Gill, Alex Brooks, Nikoli Dryden, Andrew Lenharth, Loc Hoang, Keshav Pingali, Marc Snir

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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.

Original languageEnglish (US)
Title of host publicationProceedings - 2018 IEEE 32nd International Parallel and Distributed Processing Symposium, IPDPS 2018
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages980-989
Number of pages10
ISBN (Print)9781538643686
DOIs
StatePublished - Aug 3 2018
Event32nd IEEE International Parallel and Distributed Processing Symposium, IPDPS 2018 - Vancouver, Canada
Duration: May 21 2018May 25 2018

Publication series

NameProceedings - 2018 IEEE 32nd International Parallel and Distributed Processing Symposium, IPDPS 2018

Other

Other32nd IEEE International Parallel and Distributed Processing Symposium, IPDPS 2018
CountryCanada
CityVancouver
Period5/21/185/25/18

Keywords

  • Clusters
  • Communication systems
  • Graph analytics

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Networks and Communications
  • Hardware and Architecture
  • Information Systems and Management

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