Representing and exploiting data parallelism using multidimensional dataflow diagrams

Authors:
Edward A. Lee
Affiliations:
Dept. of EECS, University of California, Berkeley, CA
Venue:
ICASSP'93 Proceedings of the 1993 IEEE international conference on Acoustics, speech, and signal processing: plenary, special, audio, underwater acoustics, VLSI, neural networks - Volume I
Year:
1993

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Abstract

Signal flow graphs with dataflow semantics have been used in signal processing system simulation, algorithm development, and real-time system design. Dataflow semantics implicitly expose function parallelism by imposing only a partial ordering constraint on the execution of functions. They are also capable of representing data parallelism. This paper shows how the Synchronous dataflow model [7] can be extended to multidimensional streams to represent and exploit data parallelism in signal processing applications. The resulting semantics are related to reduced dependence graphs used in systolic array design and to the stream-oriented functional languages Lucid, Sisal, and Silage. Formal properties are developed.