Hardware synthesis from dataflow graphs of signal processing systems is a growing research area as focus shifts to high level design methodologies. For data intensive systems, dataflow based synthesis can lead to an inefficient usage of memory due to the restrictive nature of synchronous dataflow and its inability to easily model data reuse. This paper explores how dataflow graph changes can be used to drive both the on-chip and off-chip memory organisation in a hardware implementation. By exploiting the data reuse inherent to many image processing algorithms and creating memory hierarchies, the off-chip memory bandwidth can be reduced by a factor of a thousand from the original dataflow graph level specification of a motion estimation algorithm with a minimal increase in memory size.
This paper describes the Muir hardware synthesis process used in the Abhainn design flow for optimisation and implementation of applications on FPGA-centric platforms and specifically its use for multimedia applications. Demonstrated are transformations available at the algorithmic level for an MPEG-2 encoder to reduce the memory usage and increase the throughput of the system. Also examined is the effect manipulations of the algorithm have on the final hardware architecture. Implementation of the encoder shows that results derived from a system level design approach are comparable with those derived from hand-coded implementations.
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