Sanjay V. Kumar

Impact of NBTI on SRAM Read Stability and Design for Reliability

Negative bias temperature instability (NBTI) has the potential to become one of the main show-stoppers of circuit reliability in nanometer scale devices due to its deleterious effects on transistor threshold voltage. The degradation of PMOS devices due to NBTI leads to reduced temporal performance in digital circuits. We have analyzed the impact of NBTI on the read stability of SRAM cells. The amount of degradation in static noise margin (SNM) which is a measure of the read stability of the 6-T SRAM cell has been estimated using reaction-diffusion (R-D) model. We propose a simple solution to recover the SNM of the SRAM cell using a data flipping technique and present the results simulated on BPTM 70nm and 100nm technology. We also compare and evaluate different implementation methodologies for the proposed technique

An analytical model for negative bias temperature instability

Negative bias temperature instability (NBTI) in PMOS transistors has become a significant reliability concern in present day digital circuit design. With continued scaling, the effect of NBTI has rapidly grown in prominence, forcing designers to resort to a pessimistic design style using guard-banding. Since NBTI is strongly dependent on the time for which the PMOS device is stressed, different gates in a combinational circuit experience varying extents of delay degradation. This has necessitated a mechanism of quantizing the gate-delay degradation, to pave the way for improved design strategies. Our work addresses this issue by providing a procedure for determining the amount of delay degradation of a circuit due to NBTI. An analytical model for NBTI is derived using the framework of the reaction-diffusion model, and a mathematical proof for the widely observed phenomenon of frequency independence is provided. Simulations on ISCAS benchmarks under a 70nm technology show that NBTI causes a delay degradation of about 8% in combinational logic based circuits after 10 years (ap 3 times 108s)

NBTI-aware synthesis of digital circuits

Negative bias temperature instability (NBTI) in PMOS transistors has become a major reliability concern in nanometer scale design, causing the temporal degradation of the threshold voltage of the PMOS transistors, and the delay of digital circuits. A novel method to characterize the delay of every gate in the standard cell library, as a function of the signal probability of each of its inputs, is developed. Accordingly, a technology mapping technique that incorporates the NBTI stress and recovery effects, in order to ensure optimal performance of the circuit, during its entire lifetime, is presented. Our technique, demonstrated over 65 nm benchmarks shows an average of 10 % area recovery, and 12 % power savings, as against a pessimistic method that assumes constant stress on all PMOS transistors in the design.

Adaptive techniques for overcoming performance degradation due to aging in digital circuits

Negative Bias Temperature Instability (NBTI) in PMOS transistors has become a major reliability concern in present-day digital circuit design. Further, with the recent usage of Hf-based high-k dielectrics for gate leakage reduction, Positive Bias Temperature Instability (PBTI), the dual effect in NMOS transistors has also reached significant levels. Consequently, designers are required to build in substantial guard-bands into their designs, leading to large area and power overheads, in order to guarantee reliable operation over the lifetime of a chip. We propose a guard-banding technique based on adaptive body bias (ABB) and adaptive supply voltage (ASV), to recover the performance of an aged circuit, and compare its merits over previous approaches.

Adaptive Techniques for Overcoming Performance Degradation Due to Aging in CMOS Circuits

Negative bias temperature instability (NBTI) in pMOS transistors has become a major reliability concern in present-day digital circuit design. Further, with the recent introduction of Hf-based high-k dielectrics for gate leakage reduction, positive bias temperature instability (PBTI), the dual effect in nMOS transistors, has also reached significant levels. Consequently, designs are required to build in substantial guardbands in order to guarantee reliable operation over the lifetime of a chip, and these involve large area and power overheads. In this paper, we begin by proposing the use of adaptive body bias (ABB) and adaptive supply voltage (ASV) to maintain optimal performance of an aged circuit, and demonstrate its advantages over a guard banding technique such as synthesis. We then present a hybrid approach, utilizing the merits of both ABB and synthesis, to ensure that the resultant circuit meets the performance constraints over its lifetime, and has a minimal area and power overhead, as compared with a nominally designed circuit.

Body Bias Voltage Computations for Process and Temperature Compensation

With continued scaling into the sub-90-nm regime, the role of process, voltage, and temperature (PVT) variations on the performance of VLSI circuits has become extremely important. These variations can cause the delay and the leakage of the chip to vary significantly from their expected values, thereby affecting the yield. Circuit designers have proposed the use of threshold voltage modulation techniques to pull back the chip to the nominal operational region. One such scheme, known as adaptive body bias (ABB), has become extremely effective in ensuring optimal performance or leakage savings. Our work provides a means to efficiently compute the body bias voltages required for ensuring high performance operation in gigascale systems. We provide a computer-aided design (CAD) perspective for determining the exact amount of bias voltages that can compensate both temperature and process variations. Mathematical models for delay and leakage based on minimal tester measurements are built, and a nonlinear optimization problem is formulated to ensure highest frequency operation under all conditions, and thereby minimize the overall circuit leakage. Three different algorithms are presented and their accuracies and runtimes are compared. The algorithms have been applied to a wide range of process and temperature corners, for a 65- and 45-nm technology node-based process. A suitable implementation mechanism has also been outlined.

Mathematically assisted adaptive body bias (ABB) for temperature compensation in gigascale LSI systems

Process variations and temperature variations can cause both the frequency and the leakage of the chip to vary significantly from their expected values, thereby decreasing the yield. Adaptive body bias (ABB) can be used to pull back the chip to the nominal operational region. We propose the use of this technique to counter temperature variations along with process variations. We present a CAD perspective for achieving process and temperature compensation using bidirectional ABB. Mathematical models are used to determine the exact amount of body bias required optimizing the delay and leakage, and an algorithmic flow that can be adopted for gigascale LSI systems is provided

A Finite-Oxide Thickness-Based Analytical Model for Negative Bias Temperature Instability

Negative bias temperature instability (NBTI) in PMOS transistors has become a serious reliability concern in present-day digital circuit design. With continued technology scaling, and reducing oxide thickness, it has become imperative to accurately determine its effects on temporal circuit degradation, and thereby ensure reliable operation for a finite period of time. A reaction-diffusion (R-D)-based framework is developed for determining the number of interface traps as a function of time, for both the dc (static NBTI) and the ac (dynamic NBTI) stress cases. The effects of finite oxide thickness, and the influence of trap generation and annealing in polysilicon, are incorporated. The model provides a good fit with experimental data and also provides a satisfying explanation for most of the physical effects associated with the dynamics of NBTI. A generalized framework for estimating the impact of NBTI-induced temporal degradation in present-day digital circuits, is also discussed.

Thermally Aware Design

With greater integration, the power dissipation in integrated circuits has begun to outpace the ability of todays heat sinks to limit the on-chip temperature. As a result, thermal issues have come to the forefront, and thermally aware design techniques are likely to play a major role in the future. While improved heat sink technologies are available, economic considerations restrict them from being widely deployed until and unless they become more cost-effective. Low power design is helpful in controlling on-chip temperatures, but is already widely utilized, and new thermal-specific approaches are necessary. In short, the onus on thermal management is beginning to move from the package designer toward the chip designer. This survey provides an overview of analysis and optimization techniques for thermally aware design. After beginning with a motivation for the problem and trends seen in the semiconductor industry, the survey presents a description of techniques for on-chip thermal analysis. Next, the effects of elevated temperatures on on-chip performance metrics are analyzed. Finally, a set of thermal optimization techniques, for controlling on-chip temperatures and limiting the level to which they degrade circuit performance, are described.

A framework for block-based timing sensitivity analysis

Since process and environmental variations can no longer be ignored in high-performance microprocessor designs, it is necessary to develop techniques for computing the sensitivities of the timing slacks to parameter variations. This additional slack information enables designers to examine paths that have large sensitivities to various parameters: such paths are not robust, even though they may have large nominal slacks and may hence be ignored in traditional timing analysis. We present a framework for block-based timing analysis, where the parameters are specified as ranges - rather than statistical distributions which are hard to know in practice. We show that our approach - which scales well with the number of processors - is accurate at all values of the parameters within the specified bounds, and not just at the worst- case corner. This allows the designers to quantify the robustness of the design at any design point. We validate our approach on circuit blocks extracted from a commercial 45 nm microprocessor.