ColdCode: Cold Data Encoding for Enhanced Reliability and Lifetime in 3D NAND Flash
Published in European Conference on Computer Systems (Eurosys), 2026
Cold storage, which stores rarely accessed data, dominates modern data centers but is poorly served by NAND flash’s data randomization. As a common practice today by flash vendors, data randomization is applied in NAND flash chips to avoid extreme data patterns that generate the worst-case raw bit error rate (RBER). However, this paper demonstrates that data randomization rules out the opportunity to explore data patterns with very low RBERs, through a comprehensive analysis on data randomization in 3D NAND flash chips (across 8 models). Motivated by this, we propose ColdCode, a novel data coding framework to replace the conventional randomizer in 3D high-density flash for cold data storage. Using a tag that indicates coldness information passed from the file system to solid-state drive (SSD) controllers, the controller encodes cold data to enhance reliability and extend lifetime. ColdCode employs two coding techniques: skewed coding and reversed Huffman coding, applied based on the data entropy. These techniques effectively reduce the RBER of encoded data compared to conventional randomization. Experimental results on real high-density 3D flash chips show that, under the same error conditions, the skewed coding and reversed Huffman coding reduce the average RBER by 42% and 30%, respectively. Consequently, the lifetime of the flash chips is prolonged by factors of 2.8× and 1.7×, respectively, compared to data randomization.
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