SPIDER: Sizing-Priority-Based Application-Driven Memory for Mobile Video Applications

Recently, mobile devices such as smartphones and tablets have become the most important medium for delivering internet traffic, especially multimedia content, to end users. However, mobile embedded memory incurs large power consumption owing to the highly frequent access and extensive computation. This paper presents an sizing-priority-based application-driven memory (SPIDER) design methodology for low-power mobile video applications. We investigate the size dependent memory failure characteristics and effectively reduce the memory failure rate with low area overhead. Also, we develop a model for the influence of the memory failure on video output, connecting the hardware design process and application requirement. Based on this, we design the SPIDER algorithms for area-priority and quality-priority mobile video applications. During this process, we also consider the contribution of both Luma and Chroma to output quality, avoiding over-optimization issue. We also develop a hardware-based python-assisted SPIDER simulator to apply our proposed design in one leading edge video compression system, the H.264 decoder. Our simulation results in 45-nm CMOS technology show that SPIDER supports mobile videos successfully as voltage downs to 500 mV from 1 V, enabling over 70% power savings in memory arrays.