Rouwaida Kanj

Mixture importance sampling and its application to the analysis of SRAM designs in the presence of rare failure events

In this paper, we propose a novel methodology for statistical SRAM design and analysis. It relies on an efficient form of importance sampling, mixture importance sampling. The method is comprehensive, computationally efficient and the results are in excellent agreement with those obtained via standard Monte Carlo techniques. All this comes at significant gains in speed and accuracy, with speedup of more than 100times compared to regular Monte Carlo. To the best of our knowledge, this is the first time such a methodology is applied to the analysis of SRAM designs

The Impact of Aging Effects and Manufacturing Variation on SRAM Soft-Error Rate

This paper describes modeling and hardware results of how the soft-error rate (SER) of a 65-nm silicon-on-insulator SRAM memory cell changes over time, as semiconductor aging effects shift the SRAM cell behavior. This paper also describes how the SER changes in the presence of systematic and random manufacturing variation.

Cross Layer Error Exploitation for Aggressive Voltage Scaling

This paper shows that by co-designing circuits and systems, considerable power savings are possible if the inherent data redundancy of candidate systems such as wireless is used to compensate for hardware failures. A comprehensive study of 6T SRAM failure modes is presented. The generated statistics are used to quantify a power savings of up to 17.5% for a case study of a 32 nm CMOS 3 GPP WCDMA modem

System-Level SRAM Yield Enhancement

It is well known that SRAM constitutes a large portion of modern integrated circuits, with 80% or more of the total transistors being dedicated to SRAM in a typical processor or SOC. Thus yield management of these SRAMs plays a crucial role in insuring design success. This paper demonstrates analysis techniques to model and improve the yield of SRAMs at the system level by proper accounting for the coupling between the algorithms targeted for an SOC and the performance, power, and yield of SRAMs used in implementing the algorithms. It is shown that coupling the algorithm and SRAM design phases provides significant advantages over independent optimization

A Disturb Decoupled Column Select 8T SRAM Cell

This paper presents a novel 8 transistor SRAM cell that can be used for enhancing cell Vddmin at and beyond 90 nm technology nodes. This cell provides a way to eliminate the column select read disturb scenario in SRAMs which is one of the impediments to lowering cell voltage. Read disturbs to the selected cell are then minimized by relying on a sense-amp based array architecture which enables discharging the bit-line (BL) capacitance to GND during a read operation thereby enhancing its low voltage operability. The sensitivity of the cell to BL height and sense timing has been studied and the feasibility of the cell has been proved by fabricating a 32 Kb array in a 90 nm PD/SOI technology. Hardware experiments and simulation results show improvements of cell Vddmin over traditional 6T cells by more than 150 mV for 90 nm PD/SOI technology.

A Novel Column-Decoupled 8T Cell for Low-Power Differential and Domino-Based SRAM Design

We present a novel half-select disturb free transistor SRAM cell. The cell is 6T based and utilizes decoupling logic. It employs gated inverter SRAM cells to decouple the column select read disturb scenario in half-selected columns which is one of the impediments to lowering cell voltage. Furthermore, “false read” before write operation, common to conventional 6T designs due to bit-select and wordline timing mismatch, is eliminated using this design. Two design styles are studied to account for the emerging needs of technology scaling as designs migrate from 90 to 65 nm PD/SOI technology nodes. Namely we focus on a 90 nm PD/SOI sense Amp based and 65 nm PD/SOI domino read based designs. For the sense Amp based design, read disturbs to the fully-selected cell can be further minimized by relying on a read-assist array architecture which enables discharging the bit-line (BL) capacitance to GND during a read operation. This together with the elimination of half-select disturbs enhance the overall array low voltage operability and hence reduce power consumption by 20%-30%. The domino read based SRAM design also exploits the proposed cell to enhance cell stability while reducing the overall power consumption more than 30% by relying on a dynamic dual supply technique in combination of cell design and peripheral circuitry. Because half-selected columns/cells are inherently protected by the proposed scheme, the dynamic supply “High” voltage is only applied to read selected columns/cells, while dynamic supply “Low” is employed in all other situations, thereby reducing the overall design power. A short bitline loading of 16 cells/BL is adopted to achieve high-performance low-power operation and lower bitline capacitance to improve stability. A newly developed fast Monte Carlo based statistical method is used to analyze such a unique cell, and 65 nm design simulations are carried out at 5 GHz. The feasibility of the cell and sensitivity to sense Amp timing has been proved by fabricating a 32 kb array in a 90-nm PD/SOI technology. Hardware experiments and simulation results show improvements of cell Vddmin over traditional 6T cells by more than 150 mV for 90 nm PD/SOI technology. Also experimental results based on fabricated 65 nm PD/SOI (1.6 kb/site × 80 sites) hardware also asserts half-select disturb elimination and hence the ability to enable significant power savings. The performance and speed are shown to be comparable with the conventional 6T design.

Statistical Exploration of the Dual Supply Voltage Space of a 65nm PD/SOI CMOS SRAM Cell

This paper describes the application of a novel variability-driven statistical analysis methodology to study the stability/performance of SRAM designs in 65nm PD/SOI technology. Our objective is to explore the design-yield space for wordline and bitline voltage assignments in dual supply SRAM while taking into consideration the impact of random process variations. Two possible scenarios are studied: namely wordline connected to the SRAM cell power supply, and wordline connected to the logic power supply. To the best of our knowledge this is the first time a fully statistical analysis is performed, and results are in excellent agreement with hardware measurements

A thermal and process variation aware MTJ switching model and its applications in soft error analysis

Spin-transfer torque random access memory (STT-RAM) has recently gained increased attentions from circuit design and architecture societies. Although STT-RAM offers a good combination of small cell size, nanosecond access time and non-volatility for embedded memory applications, the reliability of STT-RAM is severely impacted by device variations and environmental disturbances. In this paper, we develop a compact switching model for magnetic tunneling junction (MTJ), which is the data storage device in STT-RAM cells. By leveraging the capability to simulate the impacts of thermal and process variations on MTJ switching, our model is able to analyze the diverse mechanisms of STT-RAM write operation failures. Besides the impacts of thermal and process variation, the soft error induced by radiation striking on the access transistor is another important threat to the MTJ reliability. It can also be analyzed by using our model. The incurred computation cost of our model is much less than the conventional macro-magnetic model, and hence, enabling its applications in comprehensive STT-RAM reliability analysis and design optimizations.

FinFET SRAM Design

This paper describes the SRAM design concept in FinFETtechnologies using unique features of non-planar double-gated devices. The parameter space required to design FinFETs is explored.Variety of SRAM design techniques are presented exploiting the advantages of tied gate and independent gate controlled configurations. SRAM performance, power, and stability for FinFET devices are compared with conventional planar CMOS counterparts. Modeling the variability of FinFETs through statistics is presented as well.

An elegant hardware-corroborated statistical repair and test methodology for conquering aging effects

We propose a new and efficient statistical-simulation-based test methodology for optimally selecting repair elements at beginning-of-life (BOL) to improve the end-of-life (EOL) functionality of memory designs. This is achieved by identifying the best BOL test/repair corner that maximizes EOL yield, thereby exploiting redundancy to optimize EOL operability with minimal BOL yield loss. The statistical approach makes it possible to identify such corners with tremendous savings in terms of test time and hardware. To estimate yields and search for the best repair corner the approach relies on fast conditional importance sampling statistical simulations. The methodology is versatile and can handle complex aging effects with asymmetrical distributions. Results are demonstrated on state-of-the-art dual-supply memory designs subject to statistical negative bias temperature instability (NBTI) effects, and hardware results are shown to match predicted model trends.