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T-thinker: A task-centric distributed framework for compute-intensive divide-and-conquer algorithms

  • Da Yan
  • , Guimu Guo
  • , Md Mashiur Rahman Chowdhury
  • , M. Tamer Ozsu
  • , John C.S. Lui
  • , Weida Tan

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

Abstract

Many computationally expensive problems are solved by a divide-and-conquer algorithm: a problem over a big dataset can be recursively divided into independent tasks over smaller subsets of the dataset. We present a distributed generalpurpose framework called T-thinker which effectively utilizes the CPU cores in a cluster by properly decomposing an expensive problem into smaller independent tasks for parallel computation. T-thinker well overlaps CPU processing with network communication, and its superior performance is verified over a re-engineered graph mining system G-thinker available at http://cs.uab.edu/yanda/gthinker/.

Original languageEnglish (US)
Title of host publicationPPoPP 2019 - Proceedings of the 24th Principles and Practice of Parallel Programming
PublisherAssociation for Computing Machinery
Pages411-412
Number of pages2
ISBN (Electronic)9781450362252
DOIs
StatePublished - Feb 16 2019
Externally publishedYes
Event24th ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming, PPoPP 2019 - Washington, United States
Duration: Feb 16 2019Feb 20 2019

Publication series

NameProceedings of the ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming, PPOPP
ISSN (Print)1542-0205

Conference

Conference24th ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming, PPoPP 2019
Country/TerritoryUnited States
CityWashington
Period2/16/192/20/19

All Science Journal Classification (ASJC) codes

  • Software

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