| Summary: | The increasing integration of functional blocks in today's integrated circuit designs necessitates a large embedded memory for data manipulation and storage. The most often used embedded memory is the Static Random Access Memory (SRAM), with a six transistor memory bit-cell. Currently, memories occupy more than 50% of the chip area and this percentage is only expected to increase in future. Therefore, for the silicon vendors, it is critical that the memory units yield well, to enable an overall high yield of the chip. The increasing memory density is accompanied by aggressive scaling of the transistor dimensions in the SRAM. Together, these two developments make SRAMs increasingly susceptible to process-parameter variations. As a result, in the current nanometer regime, statistical methods for the design of the SRAM array are pivotal to achieve satisfactory levels of silicon predictability.
In this work, a method for the statistical design of the SRAM bit-cell is proposed. Not only does it provide a high yield, but also meets the specifications for the design constraints of stability, successful write, performance, leakage and area. The method consists of an optimization framework, which derives the optimal design parameters; i.e., the widths and lengths of the bit-cell transistors, which provide maximum immunity to the variations in the transistor's geometry and intrinsic threshold voltage fluctuations. The method is employed to obtain optimal designs in the 65nm, 45nm and 32nm technologies for different set of specifications. The optimality of the resultant designs is verified. The resultant optimal bit-cell designs in the 65nm, 45nm and 32nm technologies are analyzed to study the SRAM area and yield trade-offs associated with technology scaling. In order to achieve 50% scaling of the bit-cell area, at every technology node, two ways are proposed. The resultant designs are further investigated to understand, which mode of failure in the bit-cell becomes more dominant with technology scaling. In addition, the impact of voltage scaling on the bit-cell designs is also studied.
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