Process Corners Analysis of Data Retention Voltage (DRV) for 6T, 8T, and 10T SRAM Cells at 45 nm

ABSTRACT The quest for low power increases with the advancement in technology as a result of continuous device scaling. Static random access memory (SRAM) represents the technology workhorse due to its compatibility with the logic. Denser SRAM is required for modern high performance applications. The stability of SRAM in low power regime needs attention due to increasing effects of process variations in low dimensions. These variations are steep for the scaled devices. Data retention voltage (DRV) is the main parameter for SRAM to estimate the cell stability. This paper analyses the stability of SRAM in terms of process corner analysis of DRV. The process corner analysis in addition to temperature analysis is carried out with the Cadence Virtuoso tool using the 45 nm generic process design kit (GPDK) technology file. At lower temperature, the DRV is lowest at the FF process corner and highest at the SS corner. But for higher temperature, the highest value of DRV is obtained at the SF corner. Similarly, with varying cell ratio (CR), the process corner analysis shows that FF and TT are the best corners for low power operations.

[1]  Zhi-Hui Kong,et al.  An 8T Differential SRAM With Improved Noise Margin for Bit-Interleaving in 65 nm CMOS , 2011, IEEE Transactions on Circuits and Systems I: Regular Papers.

[2]  Ricardo Reis,et al.  Protecting Chips Against Hold Time Violations Due to Variability , 2013 .

[3]  Jiajing Wang,et al.  Techniques to Extend Canary-Based Standby $V_{DD}$ Scaling for SRAMs to 45 nm and Beyond , 2008, IEEE Journal of Solid-State Circuits.

[4]  Hiroyuki Yamauchi A Discussion on SRAM Circuit Design Trend in Deeper Nanometer-Scale Technologies , 2010, IEEE Transactions on Very Large Scale Integration (VLSI) Systems.

[5]  Kaushik Roy,et al.  A 32 kb 10T Sub-Threshold SRAM Array With Bit-Interleaving and Differential Read Scheme in 90 nm CMOS , 2009, IEEE Journal of Solid-State Circuits.

[6]  Mohd. Hasan,et al.  A technique to mitigate impact of process, voltage and temperature variations on design metrics of SRAM Cell , 2012, Microelectron. Reliab..

[7]  Mohab Anis,et al.  Statistical Design of the 6T SRAM Bit Cell , 2010, IEEE Transactions on Circuits and Systems I: Regular Papers.

[8]  Jan M. Rabaey,et al.  Standby supply voltage minimization for deep sub-micron SRAM , 2005, Microelectron. J..

[9]  Petru Andrei,et al.  Sensitivity of static noise margins to random dopant variations in 6-T SRAM cells , 2008 .

[10]  Asen Asenov,et al.  Impact of intrinsic parameter fluctuations in decanano MOSFETs on yield and functionality of SRAM cells , 2005 .

[11]  William H. Robinson,et al.  Impact of Process Variations on Reliability and Performance of 32-nm 6T SRAM at Near Threshold Voltage , 2014, 2014 IEEE Computer Society Annual Symposium on VLSI.