[ADA+12] Parallel patterns + Macro Data Flow for multi-core programming

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

@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}, }

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 »
In	Proc. of Intl. Euromicro PDP 2012: Parallel Distributed and network-based Processing
Page(s)	27-36
Year	2012
Publisher	IEEE
Address	Garching, Germany
URL	http://calvados.di.unipi.it/storage/paper_files/2012_mdf_PDP.pdf