Efficient Bad Block Management with Cluster Similarity
Jui-Nan Yen, Yao‐Ching Hsieh, Cheng‐Yu Chen, Tseng‐Yi Chen, Chia-Lin Yang, Hsiang-Yun Cheng, Yixin Luo · 2022
Process variation in the 3D flash memory architecture raises the difficulty of bad block management. Since the error characteristics vary among different blocks, it is difficult for the existing P/E cycle-based bad block management policies to decide a suitable cycle threshold. This increases the possibility of data loss and decreases the SSD’s lifetime. In this work, we characterize the 3D flash memory and observe spatial correlation among flash blocks in the aspect of error behaviors. This phenomenon is referred to as cluster similarity. A novel cluster-based bad block management policy is proposed, which treats the failure of a block as an indicator of near-future failures of its neighboring blocks. Moreover, we provide quantitative methods to enable judicious selection of the cluster size to meet the desired tradeoff between the SSD lifetime and reliability. Compared with the commonly-used cycle-based bad block management policy, our cluster-based management policy has a lifetime improvement of 2x with comparable failure rates. And with comparable lifetime, the failure rate of the cycle-based policy is 9x higher than our method. To alleviate the I/O performance impact caused by the cluster retirement, we proposes a critical-block first reallocation scheduling. Our experiments show up to two times improvement of the 95th percentile latency compared to the naive scheduling of cluster reallocation.