Approximate image storage with multi-level cell STT-MRAM main memory

作者：Hengyu Zhao, Linuo Xue, Ping Chi, Jishen Zhao · 年份：2017 · DOI：10.1109/iccad.2017.8203788 · 被引用次数：17 · 研究领域：Parallel Computing and Optimization Techniques、Advanced Memory and Neural Computing、Advanced Data Storage Technologies

Images consume significant storage and space in both consumer devices and in the cloud. As such, image processing applications impose high energy consumption in loading and accessing the image data in the memory. Fortunately, most image processing applications can tolerate approximate image data storage. In addition, multi-level cell spin-transfer torque MRAM (STT-MRAM) offers unique design opportunities as the image memory: the two bits in the memory cell require asymmetric write current - the soft bit requires much less write current than the hard bit. This paper proposes an approximate image processing scheme that improves system energy efficiency without upsetting image quality requirement of applications. Our design consists of (i) an approximate image storage mechanism that strives to only write the soft bits in MLC STT-MRAM main memory with small write current and (ii) a memory mode controller that determines the approximation of image data and coordinates across precise/approximate memory access modes. Our experimental results with various image processing functionalities demonstrate that our design reduces memory access energy consumption by 53% and 2.3× with 100% user's satisfaction compared with traditional DRAM-based and MLC phase-change-memory-based main memory, respectively.