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Coded distributed computing: Fundamental limits and practical challenges

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

Abstract

In this paper, we demonstrate a coded computing framework, named Coded Distributed Computing (CDC), which optimally trades extra computation resources for communication bandwidth in a MapReduce-type distributed computing environment. We also empirically illustrate the practical impact of CDC by analyzing the performance of a distributed sorting algorithm, named CodedTeraSort, which was developed by integrating the coding principle of CDC into the Hadoop benchmark TeraSort. Experiment results illustrate 1.97×-3.39 × speedup using CodedTeraSort, compared with TeraSort, for typical settings of interest. In the end, we review some of the open problems and future directions.

Original languageEnglish (US)
Title of host publicationConference Record of the 50th Asilomar Conference on Signals, Systems and Computers, ACSSC 2016
EditorsMichael B. Matthews
PublisherIEEE Computer Society
Pages509-513
Number of pages5
ISBN (Electronic)9781538639542
DOIs
StatePublished - Mar 1 2017
Externally publishedYes
Event50th Asilomar Conference on Signals, Systems and Computers, ACSSC 2016 - Pacific Grove, United States
Duration: Nov 6 2016Nov 9 2016

Publication series

NameConference Record - Asilomar Conference on Signals, Systems and Computers
ISSN (Print)1058-6393

Other

Other50th Asilomar Conference on Signals, Systems and Computers, ACSSC 2016
Country/TerritoryUnited States
CityPacific Grove
Period11/6/1611/9/16

Bibliographical note

Publisher Copyright:
© 2016 IEEE.

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