%0 Conference Paper
%B 2010 IEEE Workshop on Signal Processing Systems (SIPS)
%D 2010
%T Scalable representation of dataflow graph structures using topological patterns
%A Sane, N.
%A Kee, Hojin
%A Seetharaman, G.
%A Bhattacharyya, Shuvra S.
%K arrays
%K data flow graphs
%K Dataflow graphs
%K DIF language
%K Digital signal processing
%K directed graphs
%K DSP specification languages
%K embedded signal processing design flows
%K embedded systems
%K Field programmable gate arrays
%K graphical user interface
%K Graphical user interfaces
%K High-level languages
%K modelbased design
%K optimisation
%K optimizations
%K scalable dataflow graph structures representation
%K semantics
%K Signal processing
%K Signal processing systems
%K Specification languages
%K text based languages
%K Topological patterns
%K Topology
%K Transform coding
%X Tools for designing signal processing systems with their semantic foundation in dataflow modeling often use high-level graphical user interface (GUI) or text based languages that allow specifying applications as directed graphs. Such graphical representations serve as an initial reference point for further analysis and optimizations that lead to platform-specific implementations. For large-scale applications, the underlying graphs often consist of smaller substructures that repeat multiple times. To enable more concise representation and direct analysis of such substructures in the context of high level DSP specification languages and design tools, we develop the modeling concept of topological patterns, and propose ways for supporting this concept in a high-level language. We augment the DIF language - a language for specifying DSP-oriented dataflow graphs - with constructs for supporting topological patterns, and we show how topological patterns can be effective in various aspects of embedded signal processing design flows using specific application examples.
%B 2010 IEEE Workshop on Signal Processing Systems (SIPS)
%P 13 - 18
%8 2010
%G eng