Task Parallelism and Data Distribution: An Overview of Explicit Parallel Programming Languages

  • Dounia Khaldi
  • Pierre Jouvelot
  • Corinne Ancourt
  • François Irigoin
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7760)


Efficiently programming parallel computers would ideally require a language that provides high-level programming constructs to avoid the programming errors frequent when expressing parallelism. Since task parallelism is considered more error-prone than data parallelism, we survey six popular parallel language designs that tackle this difficult issue: Cilk, Chapel, X10, Habanero-Java, OpenMP and OpenCL. Using the parallel computation of the Mandelbrot set as running example, this paper describes how the fundamentals of task parallel programming are dealt with in these languages. Our study suggests that, even though there are many keywords and notions introduced by these languages, they boil down, as far as control issues are concerned, to three key task concepts: creation, synchronization and atomicity. These languages adopt one of three memory models: shared, message passing and Partitioned Global Address Space. The paper is designed to give users and language and compiler designers an up-to-date comparative overview of current parallel languages.


Parallel language Task parallelism Mandelbrot set Cilk Chapel X10 Habanero-Java OpenMP OpenCL 


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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Dounia Khaldi
    • 1
  • Pierre Jouvelot
    • 1
  • Corinne Ancourt
    • 1
  • François Irigoin
    • 1
  1. 1.CRI, Mathématiques et systèmesMINES ParisTechFontainebleauFrance

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