Design and implementation of a multidimensional synchronous dataflow environment

Multidimensional synchronous dataflow is a model of computation where functional blocks produce and consume data on a multidimensional index space. The model can express multidimensional signal processing systems and algorithms elegantly, and is able to reveal the data parallelism of such systems in a way that raises possibilities for better multiprocessor scheduling. We have formalized definitions and specifications for a two-dimensional model and have created a single-processor simulation domain in Ptolemy. The paper discusses the design issues and methodologies we used to efficiently handle the large amounts of two-dimensional data that the systems operate upon. The primary structures used were matrices to act as buffers and submatrices to access subsets of those buffers