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

机译:支持数据模式的自我恢复多媒体存储系统,用于近阈值计算

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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%).
机译:功能强大的移动设备(如智能电话和平板设备)的日益普及,导致对视频应用程序的需求呈指数增长。但是,由于视频解码过程的密集计算,移动视频应用程序需要频繁的嵌入式存储器访问,这会消耗大量电能并限制了电池寿命。已经研究了各种低压存储技术以增强多媒体处理系统的能量效率。不幸的是,现有的研究遭受高实现复杂度和大面积开销的困扰。在本文中,我们通过研究隐藏在移动视频数据中的有意义的数据模式,提出了一种低成本的自恢复视频存储系统。具体来说,我们提出了一种二维数据模式方法来探索水平数据关联和垂直数据相关特性。基于确定的最佳数据模式,我们提出了一种简单的电路级SRAM设计,以实现低电压下的自我恢复。设计了45nm 32kb SRAM,可在接近阈值电压(0.5 V)的情况下提供良好的视频质量,而面积开销则可忽略不计(3.97%)。

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