Flash-Gen: Spatio-Temporal Generator for Flash Memory Systems

Modeling spatio-temporal read voltages with complex distortions arising from the write and read mechanisms in flash memory devices is essential for the design of signal processing and coding algorithms. In this work, we propose Flash-Gen, a data-driven approach to generating flash memory read voltages in both space and time using conditional generative networks. This generative modeling method reconstructs read voltages from an individual memory cell based on the program levels of the cell and its surrounding cells, as well as the time stamp, in a time-efficient, resource-saving, and function-comprehensive manner. We evaluate the model over a range of time stamps using the read voltage distributions, the cell level error rates, and the relative frequency of errors for patterns most susceptible to inter-cell interference (ICI) effects. We propose a flash system optimization procedure, referred to as the Flash-Gen coding workflow, that leverages reconstructed read voltages for the development of error correction codes (ECCs) and constrained codes. Experimental results demonstrate that the model accurately captures the complex spatial and temporal features of the flash memory channel. Flash-Gen coding workflow can effectively address a range of important tasks, including threshold determination, coding performance estimation, and pattern characterization.