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

3 Scopus citations

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

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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