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 language | English (US) |
|---|---|
| Title of host publication | Conference Record of the 50th Asilomar Conference on Signals, Systems and Computers, ACSSC 2016 |
| Editors | Michael B. Matthews |
| Publisher | IEEE Computer Society |
| Pages | 509-513 |
| Number of pages | 5 |
| ISBN (Electronic) | 9781538639542 |
| DOIs | |
| State | Published - Mar 1 2017 |
| Externally published | Yes |
| Event | 50th Asilomar Conference on Signals, Systems and Computers, ACSSC 2016 - Pacific Grove, United States Duration: Nov 6 2016 → Nov 9 2016 |
Publication series
| Name | Conference Record - Asilomar Conference on Signals, Systems and Computers |
|---|---|
| ISSN (Print) | 1058-6393 |
Other
| Other | 50th Asilomar Conference on Signals, Systems and Computers, ACSSC 2016 |
|---|---|
| Country/Territory | United States |
| City | Pacific Grove |
| Period | 11/6/16 → 11/9/16 |
Bibliographical note
Publisher Copyright:© 2016 IEEE.
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