Ultra-low Power FinFET SRAM Cell with improved stability suitable for low power applications

In this paper, a new 11T SRAM cell using FinFET technology has been proposed, the basic component of the cell is the 6T SRAM cell with 4 NMOS access transistors to improve the stability and also makes it a dual port memory cell. The proposed cell uses a header scheme in which one extra PMOS transistor is used which is biased at different voltages to improve the read and write stability thus, helps in reducing the leakage power and active power. The cell shows improvement in RSNM (Read Static Noise Margin) with LP8T by 2.39x at sub-threshold voltage 2.68x with D6T SRAM cell, 5.5x with TG8T. The WSNM (Write Static Noise Margin) and HM (Hold Margin) of the SRAM cell at 0.9V is 306mV and 384mV. At sub-threshold operation also it shows improvement. The Leakage power reduced by 0.125x with LP8T, 0.022x with D6T SRAM cell, TG8T and SE8T. Also, impact of process variation on cell stability is discussed

Low Power FinFET based SRAM Cell Design

With the incessant developments occurring in VLSI circuits and systems arena and power dissipation becoming a major design constraint, the power component can be considerably reduced through efficient designing of the SRAM memory elements. Nowadays, multi-gate devices such as the FinFETs play a prominent role in reducing the power dissipation that what was found realizable by the conventional CMOS devices. Additionally, the FinFETs are found to be capable of overcoming some of the major drawbacks of the conventional CMOS devices, namely, the leakage current, the sub-threshold leakage, parasitic capacitance etc. This paper uses 32nm FinFET devices for the implementation of the 6T, 7T SRAM cell architectures and the resultant power is calculated for the read and write operations, to study the comparative benefits of the use of FinFETs in the memory cells than that of the CMOS counterpart circuits. Industry standard Cadence EDA tools have been employed for the simulations. The layout designs of 6T and 7T SRAM cells have been carried out using 180nm CMOS technology library for post layout simulations

Low Leakage and PDP Optimized FinFET based 8T SRAM Design

The paper proposes a Fin Field Effect Transistors (FinFETs) based SRAM design comprising of 8 transistors. The circuit utilizes channel length of 22 nanometers. The operation of this circuit is dependent upon the control switch CS that decides the operating mode and minimizes the leakage current flowing in the cell which in turn lowers the leakage power to a minimal value of 0.331pW. The read buffer available in the design provides a different path for read mode and also enhances the Read Static Noise Margin (RSNM), thus enhancing the readability of the circuit.This design is also able to operate at a minimal voltage of 70mV, thus efficiently utilizing the power available. It also optimizes the power delay product (PDP) for both read and write operations

Expanded Noise Margin 10T SRAM Cell using Finfet Device

Static random access memory (SRAM) cells are being improved in order to increase resistance to device level changes and satisfy the requirements of low-power applications. A unique 10-transistor FinFET-based SRAM cell with single-ended read and differential write functionality is presented in this study. This cutting-edge architecture is more power-efficient than ST (Schmitt trigger) 10T or traditional 6T SRAM cells, using only 1.87 and 1.6 units of power respectively during read operations. The efficiency is attributable to a lower read activity factor, which saves electricity. The read static noise margin (RSNM) and write static noise margin (WSNM) of the proposed 10T SRAM cell show notable improvements over the 6T SRAM cell, increasing by 1.67 and 1.86, respectively. Additionally, compared to the 6T SRAM cell, the read access time has been significantly reduced by 1.96 seconds. Utilising the Cadence Virtuoso tool and an 18nm Advanced Node Process Design Kit (PDK) technology file, the design's efficacy has been confirmed. For low-power electronic systems and next-generation memory applications, this exciting 10T SRAM cell has a lot of potential

Using pMOS Pass-Gates to Boost SRAM Performance by Exploiting Strain Effects in Sub-20-nm FinFET Technologies

Strained fin is one of the techniques used to improve the devices as their size keeps reducing in new nanoscale nodes. In this paper, we use a predictive technology of 14 nm where pMOS mobility is significantly improved when those devices are built on top of long, uncut fins, while nMOS devices present the opposite behavior due to the combination of strains. We explore the possibility of boosting circuit performance in repetitive structures where long uncut fins can be exploited to increase fin strain impact. In particular, pMOS pass-gates are used in 6T complementary SRAM cells (CSRAM) with reinforced pull-ups. Those cells are simulated under process variability and compared to the regular SRAM. We show that when layout dependent effects are considered the CSRAM design provides 10% to 40% faster access time while keeping the same area, power, and stability than a regular 6T SRAM cell. The conclusions also apply to 8T SRAM cells. The CSRAM cell also presents increased reliability in technologies whose nMOS devices have more mismatch than pMOS transistors

Four-injector variability modeling of FinFET predictive technology models

The usual way of modeling variability using threshold voltage shift and drain current amplification is becoming inaccurate as new sources of variability appear in sub-22nm devices. In this work we apply the four-injector approach for variability modeling to the simulation of SRAMs with predictive technology models from 20nm down to 7nm nodes. We show that the SRAMs, designed following ITRS roadmap, present stability metrics higher by at least 20% compared to a classical variability modeling approach. Speed estimation is also pessimistic, whereas leakage is underestimated if sub-threshold slope and DIBL mismatch and their correlations with threshold voltage are not considered

Ultra Low Power Digital Circuit Design for Wireless Sensor Network Applications

Ny forskning innenfor feltet trådløse sensornettverk åpner for nye og innovative produkter og løsninger. Biomedisinske anvendelser er blant områdene med størst potensial og det investeres i dag betydelige beløp for å bruke denne teknologien for å gjøre medisinsk diagnostikk mer effektiv samtidig som man åpner for fjerndiagnostikk basert på trådløse sensornoder integrert i et ”helsenett”. Målet er å forbedre tjenestekvalitet og redusere kostnader samtidig som brukerne skal oppleve forbedret livskvalitet som følge av økt trygghet og mulighet for å tilbringe mest mulig tid i eget hjem og unngå unødvendige sykehusbesøk og innleggelser. For å gjøre dette til en realitet er man avhengige av sensorelektronikk som bruker minst mulig energi slik at man oppnår tilstrekkelig batterilevetid selv med veldig små batterier. I sin avhandling ” Ultra Low power Digital Circuit Design for Wireless Sensor Network Applications” har PhD-kandidat Farshad Moradi fokusert på nye løsninger innenfor konstruksjon av energigjerrig digital kretselektronikk. Avhandlingen presenterer nye løsninger både innenfor aritmetiske og kombinatoriske kretser, samtidig som den studerer nye statiske minneelementer (SRAM) og alternative minnearkitekturer. Den ser også på utfordringene som oppstår når silisiumteknologien nedskaleres i takt med mikroprosessorutviklingen og foreslår løsninger som bidrar til å gjøre kretsløsninger mer robuste og skalerbare i forhold til denne utviklingen. De viktigste konklusjonene av arbeidet er at man ved å introdusere nye konstruksjonsteknikker både er i stand til å redusere energiforbruket samtidig som robusthet og teknologiskalerbarhet øker. Forskningen har vært utført i samarbeid med Purdue University og vært finansiert av Norges Forskningsråd gjennom FRINATprosjektet ”Micropower Sensor Interface in Nanometer CMOS Technology”

Nano-scale TG-FinFET: Simulation and Analysis

Transistor has been designed and fabricated in the same way since its invention more than four decades ago enabling exponential shrinking in the channel length. However, hitting fundamental limits imposed the need for introducing disruptive technology to take over. FinFET - 3-D transistor - has been emerged as the first successor to MOSFET to continue the technology scaling roadmap. In this thesis, scaling of nano-meter FinFET has been investigated on both the device and circuit levels. The studies, primarily, consider FinFET in its tri-gate (TG) structure. On the device level, first, the main TCAD models used in simulating electron transport are benchmarked against the most accurate results on the semi-classical level using Monte Carlo techniques. Different models and modifications are investigated in a trial to extend one of the conventional models to the nano-scale simulations. Second, a numerical study for scaling TG-FinFET according to the most recent International Technology Roadmap of Semiconductors is carried out by means of quantum corrected 3-D Monte Carlo simulations in the ballistic and quasi-ballistic regimes, to assess its ultimate performance and scaling behavior for the next generations. Ballisticity ratio (BR) is extracted and discussed over different channel lengths. The electron velocity along the channel is analyzed showing the physical significance of the off-equilibrium transport with scaling the channel length. On the circuit level, first, the impact of FinFET scaling on basic circuit blocks is investigated based on the PTM models. 256-bit (6T) SRAM is evaluated for channel lengths of 20nm down to 7nm showing the scaling trends of basic performance metrics. In addition, the impact of VT variations on the delay, power, and stability is reported considering die-to-die variations. Second, we move to another peer-technology which is 28nm FD-SOI as a comparative study, keeping the SRAM cell as the test block, more advanced study is carried out considering the cell‘s stability and the evolution from dynamic to static metrics