Power comparison of flow-graph and distributed arithmetic based DCT architectures

Abstract

The discrete cosine transform (DCT) is widely used in image and video compression systems. Two popular approaches to implementation of DCT algorithms include use of distributed arithmetic and flow-graphs based on fast algorithms. The distributed arithmetic architectures (DAA) have been widely used in many system implementations, due to their low latency and area requirements. However, no systematic study of power, area and latency tradeoffs of the DAA and the FGA have been studied. This paper presents a systematic study of area, latency and power consumption of these two alternate architectures. It is concluded that the flow-graph architecture consumes about 39% less power compared to the distributed arithmetic architecture, at the expenses of 28% more area and a 3.75 times increase in latency. Alternatively, by reducing the level of pipelining in the flowgraph architecture the implementation consumes 13% less power, at the expense of 20% more area and a tow times increase in latency. These results have been obtained by estimating the power consumption on actual layouts with effects of parasitic capacitance included as opposed to estimation of power consumption on schematics.