Accelerating Reliability Simulation of NAND-Flash Based Solid State Drives

Reliability is an important factor to consider when designing and deploying SSDs in storage sys- tems. Both the endurance and the retention time of flash memory are impacted by the history of low-level stress and recovery patterns to Flash cells, which are determined by the workload char- acteristics, the time period over which the workload utilizes the SSD, and the FTL algorithms. Accurately assessing SSD reliability requires simulating the workload behavior over timescales that span several years, which is very time-consuming. This thesis presents a methodology that uses snapshot-based sampling and clustering techniques to reduce the simulation time while main- taining high accuracy. The methodology leverages the key insight that most of the large changes in retention time occur early in the lifetime of the SSD, whereas most of the simulation time is spent in the latter stages. This allows for simulation acceleration to be focused on the latter stages with- out significant loss of accuracy. We show that our approach provides an average speedup of 12X over detailed simulation with an error of 3.21% in the estimated mean and 6.42% in the estimated standard deviation of the retention times of the blocks in the SSD.