ABSTRACT

With CMOS process developing, the Static Random Access Memory (SRAM) suffers unavoidable degradation in terms of read and write stabilities. To optimise the memory with conventional 6-T cell in 7-nm process technology, Response Surface Method (RSM) is adopted to get the optimised relationship among the noise margin, the operating temperature, the supply voltage, the unit ratio, the pull-up ratio and the pre-charged voltage, et al. It shows that RSM approach is an effective statistical method for the optimisation of the SRAM cell, especially in the nano-scale scheme. In order to prove the superiority of the RSM approach, the noise margin variation is investigated from 90 nm to 7 nm technology nodes based on the general butterfly curves approach for the comparison. It shows that the stability of the SNM of the 6-T cell tends to be degraded with the continuous shrinkage of the process nodes. The RSM approach is demonstrated to be an effective way for the optimisation of the SRAM cell in single-digit nanometre node.

摘要

随着CMOS工艺的发展，静态随机存取存储器（SRAM）的读写稳定性不可避免地下降。采用 7-nm 工艺技术对传统 6-T 单元的存储器进行优化，采用响应面法 (RSM) 得到噪声容限、工作温度、电源电压、单位比、上比率和预充电电压等。这表明 RSM 方法是一种有效的 SRAM 单元优化统计方法，特别是在纳米级方案中。为了证明 RSM 方法的优越性，在一般蝶形曲线方法的基础上，研究了 90 nm 到 7 nm 技术节点的噪声容限变化，以进行比较。表明随着工艺节点的不断缩小，6-T电池的SNM稳定性趋于下降。RSM方法被证明是优化个位数纳米节点的SRAM单元的有效方法。