| Abstract | Dataflow is a well known computational model and is widely used forexpressing the functionality of digital signal processing (DSP)
applications, such as audio and video data stream processing, digital
communications, and image processing. These applications usually
require real-time processing capabilities and have critical performance
constraints. Dataflow provides a formal mechanism for describing
specifications of DSP applications, imposes minimal data-dependency
constraints in specifications, and is effective in exposing and
exploiting task or data level parallelism for achieving high performance
implementations.
To demonstrate dataflow-based design methods in a manner that is
concrete and easily adapted to different platforms and back-end design
tools, we present in this report a number of case studies based on the
lightweight dataflow (LWDF) programming methodology. LWDF is designed as
a "minimalistic" approach for integrating coarse grain dataflow
programming structures into arbitrary simulation- or platform-oriented
languages, such as C, C++, CUDA, MATLAB, SystemC, Verilog, and VHDL. In
particular, LWDF requires minimal dependence on specialized tools or
libraries. This feature --- together with the rigorous adherence to
dataflow principles throughout the LWDF design framework --- allows
designers to integrate and experiment with dataflow modeling approaches
relatively quickly and flexibly into existing design methodologies and
processes.
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