Improved Computation-Communication Trade-Off for Coded Distributed Computing using Linear Dependence of Intermediate Values

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

Abstract

In large scale distributed computing systems, communication overhead is one of the major bottlenecks. In the map- shuffle-reduce framework, which is one of the major distributed computing frameworks, the communication load among servers can be reduced by increasing the computation load of each server, that is, there is a trade-off between computation load and communication load. Recently, it has been shown that coded distributed computing (CDC) improves this trade-off relationship by letting servers encode their intermediate computation results. The original CDC scheme does not assume any special structures on the functions that servers compute. However, in actual problems, these functions often have some structures, and the trade-off relation may be further improved by using that structures. In this paper, we propose a new scheme that further improves the trade-off relationship by utilizing the linear dependency structure of the intermediate computation results. The intermediate values computed in the map phase can be considered as vectors on {F}-2}. In some applications, these intermediate values have a linear dependency and in such cases, it is sufficient for each server to send a basis of the linear subspace and linear combination coefficients. As a result, the proposed approach improves over the best-known computation-communication overhead trade-off in some applications.

Original languageEnglish
Title of host publication2020 IEEE International Symposium on Information Theory, ISIT 2020 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages179-184
Number of pages6
ISBN (Electronic)9781728164328
DOIs
Publication statusPublished - 2020 Jun
Event2020 IEEE International Symposium on Information Theory, ISIT 2020 - Los Angeles, United States
Duration: 2020 Jul 212020 Jul 26

Publication series

NameIEEE International Symposium on Information Theory - Proceedings
Volume2020-June
ISSN (Print)2157-8095

Conference

Conference2020 IEEE International Symposium on Information Theory, ISIT 2020
CountryUnited States
CityLos Angeles
Period20/7/2120/7/26

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Information Systems
  • Modelling and Simulation
  • Applied Mathematics

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