Data-Pattern enabled Self-Recovery multimedia storage system for near-threshold computing

The growing popularity of powerful mobile devices such as smart phones and tablet devices has resulted in the exponential growth of demand for video applications. However, due to the intensive computation of the video decoding process, mobile video applications require frequent embedded memory access, which consumes a large amount of power and limits battery life. Various low-voltage memory techniques have been investigated to enhance the energy efficiency of multimedia processing system. Unfortunately, the existing research suffers from high implementation complexity and large area overhead. In this paper, we present a low-cost self-recovery video storage system by investigating meaningful data patterns hidden in mobile video data. Specifically, we propose a two-dimensional data-pattern approach to explore horizontal data-association and vertical data-correlation characteristics. Based on the identified optimal data patterns, we present a simple circuit-level SRAM design to enable self-recovery at low voltages. A 45nm 32kb SRAM is designed that delivers good video quality at near-threshold voltage (0.5 V) with negligible area overhead (3.97%).