Resource allocation for data-parallel computing in networks with data locality

Weina Wang, Lei Ying

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

1 Scopus citations

Abstract

This paper studies resource allocation for data-parallel applications in a networked computing system with data locality. Data-parallel computing tasks have two components: data and computation. To support efficient data-processing in the system, the resource allocation algorithm should jointly consider load-balancing, data transmissions and processing scheduling. In this paper, we consider a general model of a computing system where the computing system is a network represented by a graph, with nodes being computing devices or switches and edges being communication links. The data chunks stored at the nodes can be processed locally or be transmitted to other computing nodes in the network to be processed. The throughput of such a system for processing data-parallel applications is determined jointly by the computing capacity of the nodes and the communication capacity of the network, and the resource allocation algorithm should strike a right balance between computing and communication. In this paper, we propose a throughput-optimal resource allocation algorithm, which is also able to control the tradeoff between the expected amount of data transmitted and the expected number of backlogged tasks in steady state through a parameter qth. We show that the gap between the expected data transmission rate under our algorithm and the optimal value is O(1/qth), while the expected number of total backlogged tasks is upper bounded by O(qth).

Original languageEnglish (US)
Title of host publication54th Annual Allerton Conference on Communication, Control, and Computing, Allerton 2016
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages933-939
Number of pages7
ISBN (Electronic)9781509045495
DOIs
StatePublished - Feb 10 2017
Event54th Annual Allerton Conference on Communication, Control, and Computing, Allerton 2016 - Monticello, United States
Duration: Sep 27 2016Sep 30 2016

Publication series

Name54th Annual Allerton Conference on Communication, Control, and Computing, Allerton 2016

Other

Other54th Annual Allerton Conference on Communication, Control, and Computing, Allerton 2016
CountryUnited States
CityMonticello
Period9/27/169/30/16

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ASJC Scopus subject areas

  • Artificial Intelligence
  • Computational Theory and Mathematics
  • Computer Networks and Communications
  • Hardware and Architecture
  • Control and Optimization

Cite this

Wang, W., & Ying, L. (2017). Resource allocation for data-parallel computing in networks with data locality. In 54th Annual Allerton Conference on Communication, Control, and Computing, Allerton 2016 (pp. 933-939). [7852334] (54th Annual Allerton Conference on Communication, Control, and Computing, Allerton 2016). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ALLERTON.2016.7852334