A 90-nm low-power 32-kB embedded SRAM with gate leakage suppression circuit for mobile applications

In sub-100-nm generation, gate-tunneling leakage current increases and dominates the total standby leakage current of LSIs based on decreasing gate-oxide thickness. Showing that the gate leakage current is effectively reduced by lowering the gate voltage, we propose a local dc level control (LDLC) for SRAM cell arrays and an automatic gate leakage suppression driver (AGLSD) for peripheral circuits. We designed and fabricated a 32-kB 1-port SRAM using 90-nm CMOS technology. The six-transistor SRAM cell size is 1.25 /spl mu/m/sup 2/. Evaluation shows that the standby current of 32-kB SRAM is 1.2 /spl mu/A at 1.2 V and room temperature. It is reduced to 7.5% of conventional SRAM.     

Process variation in embedded memories: failure analysis and variation aware architecture

With scaling of device dimensions, microscopic variations in number and location of dopant atoms in the channel region of the device induce increasingly limiting electrical deviations in device characteristics such as threshold voltage. These atomic-level intrinsic fluctuations cannot be eliminated by external control of the manufacturing process and are most pronounced in minimum-geometry transistors commonly used in area-constrained circuits such as SRAM cells. Consequently, a large number of cells in a memory are expected to be faulty due to process variations in sub-50-nm technologies. This paper analyzes SRAM cell failures under process variation and proposes new variation-aware cache architecture suitable for high performance applications. The proposed architecture adaptively resizes the cache to avoid faulty cells, thereby improving yield. This scheme is transparent to processor architecture and has negligible energy and area overhead. Experimental results on a 32 K direct map L1 cache show that the proposed architecture can achieve 93% yield compared to its original 33%. The Simplescalar simulation shows that designing the data and instruction cache using the proposed architecture results in 1.5% and 5.7% average CPU performance loss (over SPEC 2000 benchmarks), respectively, for the chips with maximum number of faulty cells which can be tolerated by our proposed scheme.     

Analysis of Read Current and Write Trip Voltage Variability From a 1-MB SRAM Test Structure

We present an area efficient test structure that allows measurement of the statistical distribution of SRAM cell read currents and write trip voltages for 1 million SRAM core cells. The data taken from measurements of wafers fabricated with a 90-nm and 65-nm CMOS process flow show that the device variations are Gaussian distributed for more than 1 million devices, covering more than 5 sigma of variation. The analysis of the measured SRAM performances validate Monte Carlo simulations.      

Weak Cell Detection in Deep-Submicron SRAMs: A Programmable Detection Technique

Embedded SRAM bit count is constantly growing limiting yield in systems-on-chip (SoCs). As technology scales into deep sub-100-nm feature sizes, the increased defect density and process spreads make stability of embedded SRAMs a major concern. This paper introduces a digitally programmable detection technique, which enables detection of SRAM cells with compromised stability [with data retention faults (DRFs) being a subset]. The technique utilizes a set of cells to modify the bitline voltage, which is applied to a cell under test (CUT). The bitline voltage is digitally programmable and can be varied in wide range, modifying the pass/fail threshold of the technique. Programmability of the detection threshold allows tracking process variations and maintaining the optimal tradeoff between test quality and test yield. The measurement results of a test chip presented in the paper demonstrate the effectiveness of the proposed technique.     

Mixed body bias techniques with fixed V/sub t/ and I/sub ds/ generation circuits

There remains a need to improve sub-1-V CMOS VLSIs with respect to variation in transistor behavior. In this paper, to minimize variation in delay and the noise margin of the circuits in processors, we propose several mixed body bias techniques using body bias generation circuits. In these circuits, either the saturation region of the current between source and drain (I/sub ds/) or the threshold voltage (V/sub t/) of PMOS/NMOS is permanently fixed, regardless of temperature range or variation in process. A test chip that featured these body bias generation circuits was fabricated using a 130-nm CMOS process with a triple-well structure. The mixed body bias techniques which keep the I/sub ds/ of the MOS in the decoder and I/O circuits of a register file fixed and maintain the V/sub t/ of the MOS in both the memory cell and domino circuits of the register file fixed resulted in positive temperature dependence of delay from -40 /spl deg/C to 125 /spl deg/C, 85% reduction of the delay variation compared with normal body bias (NBB) at V/sub DD/ = 0.8 V. In addition, the results using these techniques show a 100-mV improvement in lower operating voltage compared with NBB at -40 /spl deg/C on a 4-kb SRAM.     

基于OMP的SRAM成品率分析的分组建模方法

静态随机存取存储器(SRAM)电路的失效是极小概率事件,并且不同电路条件下的失效区域边界可能相距很远。因此,为了更高效地获得更精准的SRAM成品率预测结果,提出一种基于正交匹配追踪(OMP)算法的SRAM性能分组建模方法,并应用于典型SRAM电路成品率的预测。此方法主要根据不同SRAM电路条件下失效区域边界距离的差异将仿真数据划分为多组,之后利用OMP算法对不同组的数据分别建立多项式模型,该模型可用于对SRAM电路的成品率进行快速分析预测。与标准蒙特卡洛统计算法及基于OMP的单一建模方法相比,基于OMP的分组建模方法不仅可以缩短建模时间,提高建模准确度,还能够获得更加精确的SRAM成品率预测结果。     

Efficient testing of SRAM with optimized march sequences and a novel DFT technique for emerging failures due to process variations

With increasing inter-die and intra-die parameter variations in sub-100-nm process technologies, new failure mechanisms are emerging in CMOS circuits. These failures lead to reduction in reliability of circuits, especially the area-constrained SRAM cells. In this paper, we have analyzed the emerging failure mechanisms in SRAM caches due to transistor V/sub t/ variations, which results from process variations. Also we have proposed solutions to detect those failures efficiently. In particular, in this work, SRAM failure mechanisms under transistor V/sub t/ variations are mapped to logic fault models. March test sequences have been optimized to address the emerging failure mechanisms with minimal overhead on test time. Moreover, we have proposed a design for test circuit to complement the March test sequence for at-speed testing of SRAMs. The proposed technique, referred as double sensing, can be used to test the stability of SRAM cells during read operations. Using the proposed March test sequence along with the double sensing technique, a test time reduction of 29% is achieved, compared to the existing test techniques with the same fault coverage. We have also demonstrated that double sensing can be used during SRAM normal operation for online detection and correction of any number of random read faults.     

Device Design and Optimization Methodology for Leakage and Variability Reduction in Sub-45-nm FD/SOI SRAM

Ultrathin-body fully depleted silicon-on-insulator (UTB FD/SOI) devices have emerged as a possible candidate in sub-45-nm technologies and beyond. This paper analyzes leakage and stability of FD/SOI 6T SRAM cell and presents a device design and optimization strategy for low-power and stable SRAM applications. We show that large variability and asymmetry in threshold-voltage distribution due to random dopant fluctuation (RDF) significantly increase leakage spread and degrade stability of FD/SOI SRAM cell. We propose to optimize FD devices using thinner buried oxide (BOX) structure and lower body doping combined with negative back-bias or workfunction engineering in reducing the RDF effect. Our analysis shows that thinner BOX and cooptimization of body doping and back biasing are efficient in designing low-power and stable FD/SOI SRAM cell in sub-45-nm nodes.     

A 65-nm SoC Embedded 6T-SRAM Designed for Manufacturability With Read and Write Operation Stabilizing Circuits

In the sub-100-nm CMOS generation, a large local Vth variability degrades the 6T-SRAM cell stability, so that we have to consider this local variability as well as the global variability to achieve high-yield SRAM products. Therefore, we need to employ some assist circuits to expand the SRAM operating margin. We propose a variability-tolerant 6T-SRAM cell layout and new circuit techniques to improve both the read and the write operating margins in the presence of a large Vth variability. By applying these circuit techniques to a 0.494-mum² SRAM cell with a beta ratio of 1, which is an extremely small cell size, we can achieve a high-yield 8M-SRAM for a wide range of Vth values using a 65-nm low stand-by power (LSTP) CMOS technology     

Interconnect accelerating techniques for sub-100-nm gigascale systems

This work describes new circuits called capacitor coupling trigger and capacitor coupling accelerator (CCA) circuits used to reduce the long interconnect RC delay in sub-100-nm processes. The proposed circuits use capacitors to split the output driving paths to eliminate the short-circuit current and thus improve the signal transition time. Besides, the capacitor coupling technique is applied to adjust the gate threshold voltage of the proposed circuits and isolate the input signal from the output driving transistors. The proposed circuits are faster than the prior circuits. Furthermore, the CCA can be applied to bi-directional interface, multiports bus, field-programmable gate array interconnections, and complex dynamic logic circuits.     

A process-tolerant cache architecture for improved yield in nanoscale technologies

Process parameter variations are expected to be significantly high in a sub-50-nm technology regime, which can severely affect the yield, unless very conservative design techniques are employed. The parameter variations are random in nature and are expected to be more pronounced in minimum geometry transistors commonly used in memories such as SRAM. Consequently, a large number of cells in a memory are expected to be faulty due to variations in different process parameters. We analyze the impact of process variation on the different failure mechanisms in SRAM cells. We also propose a process-tolerant cache architecture suitable for high-performance memory. This technique dynamically detects and replaces faulty cells by dynamically resizing the cache. It surpasses all the contemporary fault tolerant schemes such as row/column redundancy and error-correcting code (ECC) in handling failures due to process variation. Experimental results on a 64-K direct map L1 cache show that the proposed technique can achieve 94% yield compared to its original 33% yield (standard cache) in a 45-nm predictive technology under /spl sigma//sub Vt-inter/=/spl sigma//sub Vt-intra/=30 mV.     

The impact of intrinsic device fluctuations on CMOS SRAM cellstability

Reductions in CMOS SRAM cell static noise margin (SNM) due to intrinsic threshold voltage fluctuations in uniformly doped minimum-geometry cell MOSFETs are investigated for the first time using compact physical and stochastic models. Six sigma deviations in SNM due to intrinsic fluctuations alone are projected to exceed the nominal SMM for sub-100-nm CMOS technology generations. These large deviations pose severe barriers to scaling of supply voltage, channel length, and transistor count for conventional 6T SRAM-dominated CMOS ASICs and microprocessors     

Analysis of hot-electron reliability and device performance in80-nm double-gate SOI n-MOSFET's

In this paper, we employ a comprehensive Monte Carlo-based simulation method to model hot-electron injection, to predict induced device degradation, and to simulate and compare the performance of two double-gate fully depleted silicon-on-insulator n-MOSFET's (one with a lightly-doped channel and one with a heavily-doped channel) and a similar lightly-doped single-gate design. All three designs have an effective channel length of 80 nm and a silicon layer thickness of 25 mm. Monte Carlo simulations predict a spatial retardation between the locations of peak hot-electron injection into the front and back oxides. Since the observed shift is a significant portion of the channel length, the retardation effect greatly influences induced degradation in otherwise well-designed SOI devices. This effect may signal an important consideration for sub-100-nm design strategy. Simulations were also conducted to compare transistor performance against a key figure of merit. Evaluation of reliability and performance results indicate that the double-gate design with a lightly doped channel offers the best tradeoff in immunity to hot-electron-induced degradation and performance     

Statistical analysis of large on-chip power grid networks by variational reduction scheme

One of the most critical challenges in today's CMOS VLSI design is the lack of predictability in chip performance at design stage. One of the process variabilities comes from the voltage drop variations in on-chip power distribution networks. In this paper, we present a novel analysis approach for computing voltage drops of large power grid networks under process variations. The new algorithm is very efficient and scalable for huge networks with a large number of variational variables. This approach, called variational extended truncated balanced realization (varETBR), is based on model order reduction techniques to reduce the circuit matrices before the variational simulation. It performs the parameterized reduction on the original system using variation-bearing subspaces. After the reduction, Monte Carlo based statistical simulation is performed on the reduced system and the statistical responses of the original system are obtained thereafter. varETBR calculates variational response Grammians by Monte Carlo based numerical integration considering both system and input source variations in generating the projection subspace. varETBR is very scalable for the number of variables and flexible for different variational distributions and ranges as demonstrated in experimental results. Experimental results, on a number of IBM benchmark circuits up to 1.6 million nodes, show that the varETBR can be 1900X faster than the Monte Carlo method and is much more scalable than one of the recently proposed approaches.     

Variability aware low leakage reliable SRAM cell design technique

This paper presents a technique for designing a low power SRAM cell. The cell achieves low power dissipation due to its series connected drivers driven by bitlines and read buffers which offer stack effect. The paper investigates the impact of process, voltage, and temperature (PVT) variations on standby leakage and finds appreciable improvement in power dissipation. It also estimates read/write delay, read stability, write-ability, and compares the results with that of standard 6T SRAM cell. The comparative study based on Monte Carlo simulation exhibits appreciable improvement in leakage power dissipation and other design metrics at the expense of 84% area overhead.     

Leakage Power Characteristics of Dynamic Circuits in Nanometer CMOS Technologies

Temperature-dependent subthreshold and gate-oxide leakage power characteristics of domino logic circuits under the influence of process parameter variations are evaluated in this paper. Preferred input vectors and node voltage states that minimize the total leakage power consumption are identified at the lower and upper extremes of a typical die temperature spectrum. New low-leakage circuit design guidelines are presented based on the results. Significantly increased gate dielectric tunneling current, as described in this paper, dramatically changes the leakage power characteristics of dynamic circuits in deeply scaled nanometer CMOS technologies. Contrary to the previously published techniques, a charged dynamic-node voltage state with low inputs is preferred for reducing the total leakage power consumption in the most widely used types of single- and dual-threshold voltage domino gates, particularly at low die temperatures. Furthermore, leakage power savings provided by the dual-threshold voltage domino logic circuit techniques based on input gating are all together reduced due to the significance of gate dielectric tunneling in sub-45-nm CMOS technologies.     

An SRAM Design in 65-nm Technology Node Featuring Read and Write-Assist Circuits to Expand Operating Voltage

This paper describes a 32-Mb SRAM that has been designed and fabricated in a 65-nm low-power CMOS Technology. The 62-mm² die features read-assist and write-assist circuit techniques that expand the operating voltage range and improve manufacturability across technology platforms. Hardware measurements demonstrate the fail-count improvements achieved by integrating these techniques. The decrease in fail-count provides a 100-mV improvement of VDDMIN during the read operation. Write operations are also improved, especially with weak NFET cell transistors. The circuit techniques have been replicated on a 72-Mb stand-alone standard SRAM product where the area overhead from the additional circuits is approximately 4%. The 32-Mb SRAM has also been successfully migrated to other yield-learning SRAMs in 45-nm bulk and SOI technologies with minimum circuit changes     

Design Considerations for PD/SOI SRAM: Impact of Gate Leakage and Threshold Voltage Variation

We present a critical study of the impact of gate tunneling currents on the yield of 65-nm partially depleted/silicon-on-insulator (PD/SOI) SRAM designs. A new gate leakage monitor structure is developed to obtain device-specific gate leakage characteristics of the SRAM cells. This allows us to explore the design space accurately with reliable process information at an early stage. By relying on supply voltage-dependent analysis, it is shown that the gate-leakage impact on the cell yield can be nonmonotonic and substantial even for nondefective devices. It is also shown that design optimizations such as increased operating voltages or shorter hierarchical bitline architecture can help alleviate the gate-leakage impact on yield. Mixture importance sampling is used to estimate yield in terms of cell writability and stability. Threshold voltage variations to model random fluctuation effects are extrapolated from hardware results.     

Design of a Process Variation Tolerant Self-Repairing SRAM for Yield Enhancement in Nanoscaled CMOS

In nanoscaled technologies, increased inter-die and intra-die variations in process parameters can result in large number of parametric failures in an SRAM array, thereby, degrading yield. In this paper, we propose a self-repairing SRAM to reduce parametric failures in memory. In the proposed technique, on-chip monitoring of leakage current and/or delay of a ring oscillator is used to determine the inter-die process corner of an SRAM die. Depending on the inter-die Vt shift, the self-repair system selects the proper body bias to reduce parametric failures. Simulations using predictive 70-nm device show that the proposed self-repairing SRAM improves design yield by 5%-40%. A test-chip is designed and fabricated in IBM 0.13-mum CMOS technology to successfully demonstrate the operation of the self-repair system.     

Leakage Minimization of SRAM Cells in a Dual-$V_t$ and Dual-$T_{rm ox}$ Technology

Aggressive CMOS scaling results in low threshold voltage and thin oxide thickness for transistors manufactured in deep submicrometer regime. As a result, reducing the subthreshold and tunneling gate leakage currents has become one of the most important criteria in the design of VLSI circuits. This paper presents a method based on dual- V t and dual- T _ox assignment to reduce the total leakage power dissipation of static random access memories (SRAMs) while maintaining their performance. The proposed method is based on the observation that read and write delays of a memory cell in an SRAM block depend on the physical distance of the cell from the sense amplifier and the decoder. Thus, the idea is to deploy different configurations of six-transistor SRAM cells corresponding to different threshold voltage and oxide thickness assignments for the transistors. Unlike other techniques for low-leakage SRAM design, the proposed technique incurs neither area nor delay overhead. In addition, it results in a minor change in the SRAM design flow. The leakage saving achieved by using this technique is a function of the values of the high threshold voltage and the oxide thickness, as well as the number of rows and columns in the cell array. Simulation results with a 65-nm process demonstrate that this technique can reduce the total leakage power dissipation of a 64 times 512 SRAM array by 33% and that of a 32 times 512 SRAM array by 40%.