Data Reuse Exploration for Low Power Motion Estimation Architecture Design in H.264 Encoder

Authors:
Yu-Han Chen;Tung-Chien Chen;Chuan-Yung Tsai;Sung-Fang Tsai;Liang-Gee Chen
Affiliations:
DSP/IC Design Lab., Graduate Institute of Electronics Engineering and Department of Electrical Engineering, National Taiwan University, Taipei, Taiwan;DSP/IC Design Lab., Graduate Institute of Electronics Engineering and Department of Electrical Engineering, National Taiwan University, Taipei, Taiwan;DSP/IC Design Lab., Graduate Institute of Electronics Engineering and Department of Electrical Engineering, National Taiwan University, Taipei, Taiwan;DSP/IC Design Lab., Graduate Institute of Electronics Engineering and Department of Electrical Engineering, National Taiwan University, Taipei, Taiwan;DSP/IC Design Lab., Graduate Institute of Electronics Engineering and Department of Electrical Engineering, National Taiwan University, Taipei, Taiwan
Venue:
Journal of Signal Processing Systems
Year:
2008

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Abstract

Data access usually leads to more than 50% of the power cost in a modern signal processing system. To realize a low-power design, how to reduce the memory access power is a critical issue. Data reuse (DR) is a technique that recycles the data read from memory and can be used to reduce memory access power. In this paper, a systematic method of DR exploration for low-power architecture design is presented. For a start, the signal processing algorithms should be formulated as the nested loops structures, and data locality is explored by use of loop analysis. Then, corresponding DR techniques are applied to reduce memory access power. The proposed design methodology is applied to the motion estimation (ME) algorithms of H.264 video coding standard. After analyzing the ME algorithms, suitable parallel architectures and processing flows of the integer ME (IME) and fractional ME (FME) are proposed to achieve efficient DR. The amount of memory access is respectively reduced to 0.91 and 4.37% in the proposed IME and FME designs, and thus lots of memory access power is saved. Finally, the design methodology is also beneficial for other signal processing systems with a low-power consideration.