{'fraction_non_alphanumeric': 0.015950920245398775, 'fraction_numerical': 0.00245398773006135, 'mean_word_length': 4.956204379562044, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
Sensing margin analysis of MLC flash memories using a novel unified statistical model

A multilevel level cell (MLC) technique for flash memories reduces the bit cost and enhances the memory density. However, it is difficult to get a required sensing margin for MLC due to the need for the tight threshold voltage control. We present a unified statistical model which can account for inter-and intra-die variations. The proposed model is implemented into SPICE to predict the distribution of performance. The sensing margin is found to increase by about 30% with optimization of sensitive transistors in the sense amplifier and high voltage regulator. The statistical optimization methodology is essential to achieve an optimal sensing margin and it is widely used for other products such as DRAM, SRAM, DDI and CIS