An efficient and composable parallel task programming library

Chun Xun Lin, Tsung Wei Huang, Guannan Guo, Martin D.F. Wong

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

Abstract

Composability is a key component to improve programmers' productivity in writing fast market-expanding applications such as parallel machine learning algorithms and big data analytics. These applications exhibit both regular and irregular compute patterns, and are often combined with other functions or libraries to compose a larger program. However, composable parallel processing has taken a back seat in many existing parallel programming libraries, making it difficult to achieve modularity in large-scale parallel programs. In this paper, we introduce a new parallel task programming library using composable tasking graphs. Our library efficiently supports task parallelism together with an intuitive task graph construction and flexible execution API set to enable reusable and composable task dependency graphs. Developers can quickly compose a large parallel program from small and modular parallel building blocks, and easily deploy the program on a multicore machine. We have evaluated our library on real-world applications. Experimental results showed our library can achieve comparable performance to Intel Threading Building Blocks with less coding effort.

Original languageEnglish (US)
Title of host publication2019 IEEE High Performance Extreme Computing Conference, HPEC 2019
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781728150208
DOIs
StatePublished - Sep 2019
Event2019 IEEE High Performance Extreme Computing Conference, HPEC 2019 - Waltham, United States
Duration: Sep 24 2019Sep 26 2019

Publication series

Name2019 IEEE High Performance Extreme Computing Conference, HPEC 2019

Conference

Conference2019 IEEE High Performance Extreme Computing Conference, HPEC 2019
CountryUnited States
CityWaltham
Period9/24/199/26/19

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Keywords

  • Multithreading
  • Parallel programming

ASJC Scopus subject areas

  • Computational Theory and Mathematics
  • Computer Networks and Communications
  • Hardware and Architecture
  • Safety, Risk, Reliability and Quality
  • Artificial Intelligence

Cite this

Lin, C. X., Huang, T. W., Guo, G., & Wong, M. D. F. (2019). An efficient and composable parallel task programming library. In 2019 IEEE High Performance Extreme Computing Conference, HPEC 2019 [8916447] (2019 IEEE High Performance Extreme Computing Conference, HPEC 2019). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/HPEC.2019.8916447