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This paper introduces an 8T single-ended SRAM cell to improve stability and decrease energy consumption. It cuts the pull-down path to the storage node written '1', enhancing the write ability. It uses an isolated read path to enhance the read stability with low power and energy consumption. At a supply voltage of 0.5 V, the read static noise margin, write margin, read energy, and write energy of the proposed cell are superior by 320%, 233%, 12%, and 26%, respectively, compared to the conventional 6T. We performed 5,000 Monte Carlo simulations in the 32 nm technology to evaluate read yields. The results show that our cell has 6.9x more yields than the conventional 6T SRAM cell. Therefore, the proposed cell can be a good option for high stability and low power/energy applications. [ABSTRACT FROM AUTHOR]

Conventional static random‐access memory (SRAM) suffers from high leakage power in advanced complementary metal‐oxide‐semiconductor nodes. Meanwhile, gain‐cell embedded dynamic random‐access memory (GC‐eDRAM) is an area‐efficient alternative to SRAM, although it requires periodic refresh cycles. In this regard, this study proposes a fin field‐effect transistor (FinFET)‐based 5T GC‐eDRAM bitcell that addresses the leakage power issue of SRAM while avoiding the bandwidth‐consuming refreshes of GC‐eDRAM. Furthermore, for the feasibility of scaling down transistors, the gain‐cell design is based on the FinFET, which overcomes short‐channel problems. The proposed 5T bitcell provides additional internal feedback relative to the 4T all‐nMOS fully depleted‐silicon on insulator (FD‐SOI) gain cell to ensure the static retention of both "1" and "0" data. The 2‐kB array was simulated by employing a 7‐nm FinFET predictive technology model (PTM) using HSPICE. The simulation results show that the proposed 5T bitcell (at 0.7 V) enables over 13× smaller data retention power and 10× area reduction compared to the 4T all‐nMOS GC‐eDRAM cell in a 28‐nm FD‐SOI technology. [ABSTRACT FROM AUTHOR]

This paper introduces a 10T single-ended SRAM cell with high stability and low static power. The read static noise margin is augmented by using a Schmitt-trigger inverter and decoupling the storage node from the read bitline by adding one transistor. Since writing "1" is difficult in single-ended SRAM cells, using proper capacitive coupling and also extra pMOS transistor as an access transistor mitigates the problem. To evaluate read, write, and hold yields, we performed 10,000 Monto Carlo simulations in the 32-nm technology, and the results show our cell has 7.5×, 1.4×, and 1.1 × more yields than that of the conventional 6T SRAM cell. The proposed cell also has the least static power consumption. This amount is 1.5× less than the conventional 6T at the supply voltage of 0.5 V. [ABSTRACT FROM AUTHOR]

This paper presents a low leakage power 10T single-ended SRAM cell in the sub-threshold region that improves read, write, and hold stability. While at low voltages, the write-ability is increased by temporarily floating the data node, the read stability of the cell is maintained approximately as equal as the hold state by separating the data-storage node from the read bit line by using only a single transistor. According to Simulations using HSPICE software in 10 nm FinFET technology, the read stability of the proposed cell is approximately 4.8× higher than the conventional 6T at 200 mV. Furthermore, the proposed cell is found to have the lowest static power dissipation, as it tends to be 4% lower than the standard six-transistor cell at this voltage. This study shows that the yield of the proposed cell is higher than 6σ in all operations, and supply voltages down to 200 mV. [ABSTRACT FROM AUTHOR]

In this paper, an accurate aging model for Read Static Noise Margin (RSNM) of conventional 6 transistors (6T) FinFET SRAM cell is presented. The model, which is developed based on accurate I - V formulation suitable for FinFET, considers soft oxide breakdown (SBD) as well as bias temperature instability (BTI) effects. The accuracy of the model is verified by comparing its results with those of HSPICE simulations for the 14 nm and 10 nm technologies. The results show the maximum errors of 0.63% and 0.54% for the 14 nm and 10 nm technologies, respectively, when averaged over a wide range of stress times and supply voltages. The model also may be used to accurately predict the cumulative distribution function of the RSNM in the presence of the process variation with a very small error compared to the one obtained from the Monte Carlo approach with a considerably short runtime. [ABSTRACT FROM AUTHOR]