A Power Efficient Video Encoder Using Reconfigurable Approximate Arithmetic Units

The field of approximate computing has received significant attention from the research community in the past few years, especially in the context of various signal processing applications. Image and video compression algorithms such as JPEG, MPEG, etc., are particularly attractive candidates for approximate computing since they are tolerant of computing imprecision due to human imperceptibility, which can be exploited to realize highly power-efficient implementations of these algorithms. However, existing approximate architectures typically fix the level of hardware approximation statically and are not adaptive to input data. For example, if a fixed approximate hardware configuration is used for an MPEG encoder (i.e., a fixed level of approximation), the output quality varies greatly for different input videos. This paper addresses this issue by proposing a reconfigurable approximate architecture for MPEG encoders that optimizes power consumption while maintaining a particular PSNR threshold for any video. Experimental results show that our approach of dynamically adjusting the degree of hardware approximation based on the input video respects the given quality bound (PSNR degradation of 5-20%) across different videos while achieving a power savings of 13-18% over a conventional non-approximated MPEG encoder architecture. Although the proposed reconfigurable approximate architecture is presented for the specific case of an MPEG encoder, it can be easily extended to other DSP applications.