Algorithm-based low-power and high-performance multimedia signal processing

Abstract

Low power and high performance are the two most important criteria for many signal-processing system designs, particularly in real-time multimedia applications. There have been many approaches to achieve these two design goals at many different implementation levels ranging from very-large-scale-integration fabrication technology to system design. We review the works that have been done at various levels and focus on the algorithm-based approaches for low-power and high-performance design of signal processing systems. We present the concept of multirate computing that originates from filterbank design, then show how to employ it along with the other algorithmic methods to develop low-power and high-performance signal processing systems. The proposed multirate design methodology is systematic and applicable to many problems. We demonstrate that multirate computing is a powerful tool at the algorithmic level that enables designers to achieve either significant power reduction or high throughput depending on their choice. Design examples on basic multimedia processing blocks such as filtering, source coding, and channel coding are given. A digital signal-processing engine that is an adaptive reconfigurable architecture is also derived from the common features of our approach. Such an architecture forms a new generation of high-performance embedded signal processor based on the adaptive computing model. The goal of this paper is to demonstrate the flexibility and effectiveness of algorithm-based approaches and to show that the multirate approach is an effective and systematic design methodology to achieve low-power and high throughput signal processing at the algorithmic and architectural level.