Temperature-Aware Differential Programming for Performance and Energy Optimization on 3D NAND High-Density Flash Memory

3D NAND high-density flash memory is widely used in edge computing, IoT, and automotive applications due to its high performance, low latency, and low storage cost characteristics. These scenarios require operation in extreme temperature environments, with cross-temperature read/write occurring frequently. However, cross-temperature affects programming reliability, leading to high raw bit error rates (RBER), which degrades read performance and increases energy consumption. In this paper, we propose a novel temperature-aware differential programming (TADP) scheme to optimize read performance and energy consumption under cross-temperature read/write. Specifically, first, a temperature-aware compensatory programming scheme is proposed to reduce the cross-temperature-induced degradation of RBER. Second, a layer variation-aware compensatory programming scheme is proposed to reduce the compensatory programming latency. Finally, a degraded programming scheme is proposed to enhance the temperature toughness of poorly temperature-tough word-lines by using them as MLC. Evaluated on 233-layer 3D triple-level-cell (TLC) NAND flash, TADP achieved encouraging optimizations in programming reliability, energy consumption, and read performance with minimal capacity loss.