Leveraging Approximate Data for Robust FIash Storage

With the increasing bit density and adoption of 3D NAND, flash memory suffers from increased errors. To address the issue, flash devices adopt error correction codes (ECC) with strong error correction capability, like low-density parity-check (LDPC) code, to correct errors. The drawback of LDPC is that, to correct data with a high raw bit error rate (RBER), read latency will be amplified. This work proposes to address this issue with the assistance of approximate data. First, studies have been conducted and show there are ample amount of approximate data available in flash storage. Second, a novel data organization is proposed to fortify the reliability of regular data by leaving approximate data unprotected. Finally, a new data allocation strategy and modified garbage collection scheme are presented to complete the design. The experimental results show that the proposed approach can improve read performance by 30% on average comparing to current techniques.