Experimental characterization, optimization, and recovery of data retention errors in MLC NAND flash memory

This paper summarizes our work on experimentally characterizing, mitigating, and recovering data retention errors in multi-level cell (MLC) NAND flash memory, which was published in HPCA 2015, and examines the work's significance and future potential. Retention errors, caused by charge leakage over time, are the dominant source of flash memory errors. Understanding, characterizing, and reducing retention errors can significantly improve NAND flash memory reliability and endurance. In this work, we first characterize, with real 2Y-nm MLC NAND flash chips, how the threshold voltage distribution of flash memory changes with different retention ages -- the length of time since a flash cell was programmed. We observe from our characterization results that 1) the optimal read reference voltage of a flash cell, using which the data can be read with the lowest raw bit error rate (RBER), systematically changes with its retention age, and 2) different regions of flash memory can have different retention ages, and hence different optimal read reference voltages. Based on our findings, we propose two new techniques. First, Retention Optimized Reading (ROR) adaptively learns and applies the optimal read reference voltage for each flash memory block online. The key idea of ROR is to periodically learn a tight upper bound of the optimal read reference voltage, and from there approach the optimal read reference voltage. Our evaluations show that ROR can extend flash memory lifetime by 64% and reduce average error correction latency by 10.1%. Second, Retention Failure Recovery (RFR) recovers data with uncorrectable errors offline by identifying and probabilistically correcting flash cells with retention errors. Our evaluation shows that RFR essentially doubles the error correction capability.