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Cascade Current Mirror to Improve Linearity and Consistency in SRAM In-Memory Computing
提出级联电流镜电路,提升SRAM内存计算线性度和一致性。
28nm CMOS, 0.8V, 0.9V
SRAM内存计算级联电流镜线性度一致性
▸创新点1:级联电流镜电路(电路创新)- 通过引入级联电流镜(CCM)电路,显著改善了SRAM存内计算的线性度和一致性,减少了整数非线性误差高达70%,并提高了计算一致性56.84%。
▸创新点2:双字线6T SRAM单元(电路创新)- 采用双字线设计的6T SRAM单元,结合CCM电路,进一步降低了延迟,提升了计算一致性,优化了多行读取操作的性能。
▸创新点3:电压钳位和电流比例镜像(电路创新)- 在每个位线上仅增加四个晶体管,实现了电压钳位和电流比例镜像功能,有效解决了多行读取导致的非线性问题,提升了电路稳定性。
▸创新点4:系统级验证与应用(系统创新)- 通过在卷积神经网络分类任务中验证,MNIST数据集准确率达到91%,CIFAR-10数据集准确率达到86%,证明了该技术在AI应用中的实际性能提升。
Abstract
Although multirow read is essential to achieve static random access memory (SRAM) in-memory computing (IMC), it may undermine circuit linearity and computational consistency across columns. In this study, we investigated the causes of nonlin- earity and inconsistency. Based on detailed analyses, we proposed a cascade current mirror (CCM) peripheral circuit. Only four transistors were added to each bitline (BL) for voltage clamping and proportionally mirroring the read current. In addition, a 6T SRAM cell with double word lines operating with the CCM further reduced the delay and improved the computational consistency. We applied the structure to numerous prior studies and evaluated them using the 28-nm complementary metal– oxide semiconductor process. The measurement results show that the proposed CCM can reduce the integer nonlinearity by up to 70% at 0.8-V supply, and the computational consistency is substantially improved by 56.84% at 0.9-V supply. In addition, we verified the performance improvement through classification using a convolutional neural network, achieving 91% accuracy in the MNIST and 86% accuracy in the CIFAR-10. The area overhead was 1.77% in a 512 × 512 SRAM array when integrating the proposed CCM circuit.