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dataflow:pdp:12 (In proceedings)
Author(s) Marco Aldinucci, Marco Danelutto, Lorenzo Anardu, Massimo Torquati and Peter Kilpatrick
Title« Parallel patterns + Macro Data Flow for multi-core programming »
InProc. of Intl. Euromicro PDP 2012: Parallel Distributed and network-based Processing
Page(s)27-36
Year2012
PublisherIEEE
AddressGarching, Germany
URLhttp://calvados.di.unipi.it/storage/paper_files/2012_mdf_PDP.pdf
Abstract & Keywords
Data flow techniques have been around since the early '70s when they were used in compilers for sequential languages. Shortly after their introduction they were also considered as a possible model for parallel computing, although the impact here was limited. Recently, however, data flow has been identified as a candidate for efficient implementation of various programming models on multi-core architectures. In most cases, however, the burden of determining data flow ``macro'' instructions is left to the programmer, while the compiler/run time system manages only the efficient scheduling of these instructions. We discuss a structured parallel programming approach supporting automatic compilation of programs to macro data flow and we show experimental results demonstrating the feasibility of the approach and the efficiency of the resulting ``object'' code on different classes of state-of-the-art multi-core architectures. The experimental results use different base mechanisms to implement the macro data flow run time support, from plain pthreads with condition variables to more modern and effective lock- and fence-free parallel frameworks. Experimental results comparing efficiency of the proposed approach with those achieved using other, more classical, parallel frameworks are also presented.

Keywords: fastflow

BibTeX code

@inproceedings{dataflow:pdp:12,
  month = feb,
  author = {Marco Aldinucci and Marco Danelutto and Lorenzo Anardu and Massimo
            Torquati and Peter Kilpatrick},
  keywords = {fastflow},
  booktitle = {Proc. of Intl. Euromicro PDP 2012: Parallel Distributed and
               network-based Processing},
  url = {http://calvados.di.unipi.it/storage/paper_files/2012_mdf_PDP.pdf},
  abstract = {Data flow techniques have been around since the early '70s when
              they were used in compilers for sequential languages. Shortly
              after their introduction they were also considered as a possible
              model for parallel computing, although the impact here was
              limited. Recently, however, data flow has been identified as a
              candidate for efficient implementation of various programming
              models on multi-core architectures. In most cases, however, the
              burden of determining data flow ``macro'' instructions is left to
              the programmer, while the compiler/run time system manages only
              the efficient scheduling of these instructions. We discuss a
              structured parallel programming approach supporting automatic
              compilation of programs to macro data flow and we show
              experimental results demonstrating the feasibility of the approach
              and the efficiency of the resulting ``object'' code on different
              classes of state-of-the-art multi-core architectures. The
              experimental results use different base mechanisms to implement
              the macro data flow run time support, from plain pthreads with
              condition variables to more modern and effective lock- and
              fence-free parallel frameworks. Experimental results comparing
              efficiency of the proposed approach with those achieved using
              other, more classical, parallel frameworks are also presented.},
  address = {Garching, Germany},
  title = {Parallel patterns + Macro Data Flow for multi-core programming},
  publisher = {IEEE},
  year = {2012},
  pages = {27-36},
}


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