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With the CMOS technology scaling, transistor aging has become one major issue affecting circuit reliability and lifetime. There are two major classes of existing studies that model the aging effects in the circuit delay. One is at transistor-level, which is highly accurate but very slow. The other is at gate-level, which is faster but less accurate. Moreover, most prior studies only consider a limited subset or limited value ranges of aging factors. In this paper, we propose Aadam, a fast, accurate, and versatile aging-aware delay model for generic cell libraries. In Aadam, we first use transistor-level SPICE simulations to accurately characterize the delay degradation of each library cell under a versatile set of aging factors, including both physical parameters (i.e., initial threshold voltage and transistor width/length ratio) and operating conditions (i.e., working temperature, signal probability, input signal slew range, output load capacitance range, and projected lifetime). For each library cell, we then train a feed-forward neural network (FFNN) to learn the relation between the input aging factors and output cell delay degradation. Therefore, for a given input circuit and a given combination of aging factors, we can use the trained FFNNs to quickly and accurately infer the delay degradation for each gate in the circuit. Finally, to effectively estimate the aging-aware lifetime delay of large-scale circuits, we also integrate Aadam into a state-of-the-art static timing analysis tool called OpenTimer. Experimental results demonstrate that Aadam achieves fast estimation of the aging-induced delay with high accuracy close to transistor-level simulation.

The gate length of CMOS transistors is continuing to shrink down to the sub-10nm region and operating voltages are moving toward near-threshold and even sub-threshold values. With this trend, the number of electrons responsible for the total charge of a CMOS node is greatly reduced. As a consequence, thermal fluctuations that shift a gate from its equilibrium point may no longer have a negligible impact on circuit reliability. Time-domain analysis helps understand how transient faults affect a circuit and can guide designers in producing noise-resistant circuitry. However, modeling thermal noise in the time-domain is computationally very costly. Moreover, small fluctuations in electron occupation introduce time-varying biasing point fluctuations, increasing the modeling complexity. To address these challenges, this paper introduces a new approach to modeling thermal noise directly in the time domain by developing a series of stochastic differential equations (SDE) to model various transient effects in the presence of thermal noise. In comparisons to SPICE-based simulations, our approach can provide 3 orders of magnitude speedup in simulation time, with comparable accuracy. This simulation framework is especially valuable for detecting rare events that could translate into fault-inducing noise transients. While it is computationally infeasible to use SPICE to detect such rare events due to thermal noise, we introduce a new iterative approach that allows detecting 6a events in a matter of a few hours.

Due to aging, circuit reliability has become extraordinary challenging. Reliability-aware circuit design flows do virtually not exist and even research is in its infancy. In this paper, we propose to bring aging awareness to EDA tool flows based on so-called degradation-aware cell libraries. These libraries include detailed delay information of gates/cells under the impact that aging has on both threshold voltage (V th ) and carrier mobility (μ) of transistors. This is unlike state of the art which considers V th only. We show how ignoring s degradation leads to underestimating guard-bands by 19% on average. Our investigation revealed that the impact of aging is strongly dependent on the operating conditions of gates (i.e. input signal slew and output load capacitance), and not solely on the duty cycle of transistors. Neglecting this fact results in employing insufficient guard-bands and thus not sustaining reliability during lifetime. We demonstrate that degradation-aware libraries and tool flows are indispensable for not only accurately estimating guardbands, but also efficiently containing them. By considering aging degradations during logic synthesis, significantly more resilient circuits can be obtained. We further quantify the impact of aging on the degradation of image processing circuits. This goes far beyond investigating aging with respect to path delays solely. We show that in a standard design without any guardbanding, aging leads to unacceptable image quality after just one year. By contrast, if the synthesis tool is provided with the degradation-aware cell library, high image quality is sustained for 10 years (even under worst-case aging and without a guardband). Hence, using our approach, aging can be effectively suppressed.

Dynamic voltage scaling (DVS) has become one of the most effective approaches to achieve ultra-low-power SoC. To eliminate timing errors arising from DVS, several error-resilient circuit design techniques were proposed to detect and/or correct timing violations. The most recently proposed time-borrowing-and-local-boosting (TBLB) technique has the advantage of lower power consumption and less performance degradation due to the needlessness of pipeline stalls. On the other hand, to make the best use of the TBLB technique, a special timing requirement for TBLB latches must be considered in the physical design process. To address this issue, a novel reliability-aware latch clustering method for low-power TBLB resilient circuits is introduced. Experimental results show that the proposed approach is very effective in reducing the delay of both combinational and error-detection circuits, which indicates better circuit reliability.

The ongoing shrinking of interconnects in integrated circuits (ICs) induces reliability issues caused by electromigration (EM), including void-induced failure mechanisms in IC vias. We propose a new post-routing approach to insert redundant vias specially targeted for EM avoidance. Our algorithm compares all possible insertions and utilizes the configuration with the highest reliability gain. This is achieved by considering the connecting segment loads. These loads are an estimation of the risk involved in creating EM-induced voids as a continuous function of current density, segment length and stress development over time. Inserting vias in those segments with highest loads, our approach efficiently increases circuit reliability by reducing EM effects. We were able to reduce the total, average and maximum via load for the MCNC benchmark suite on average by 6.6%, 4% and 13.9%, respectively. The increase in via reliability was confirmed by subsequent modeling of EM-inducing factors.

For the current advanced technology nodes, an accurate, yet fast reliability analysis is needed at design time, to enable the comparison between different circuit architectures, and thus a reliability-aware design and synthesis process. To this end we propose a reliability assessment framework that is able to estimate more accurately the circuit reliability and which can be applied to large-scale circuit settings, by: (i) taking into account the circuit topology (and implicitly its reconvergent fanouts), the input vectors, the environmental conditions and fault scenarios, (ii) employing a range of probabilities, i.e., a Probability Density Function (PDF), instead of hitherto single probability value, in order to quantify the circuit reliability, (iii) employing variational inference, to derive the circuit primary output PDFs, given its primary inputs PDFs, and (iv) adapting the traditional variational inference approach to exploit the peculiarities of the probabilistic model afferent to logic circuits, for convergence speed improvements and thus applicability in large scale circuits settings.

The trend towards massive parallel computing has necessitated the need for an On-Chip communication framework that can scale well with the increasing number of cores. At the same time, technology scaling has made transistors susceptible to a multitude of reliability issues (NBTI, HCI, TDDB). In this work, we propose an HCI-Tolerant microarchitecture for an NoC Router by manipulating the switching activity around the circuit. We find that most of the switching activity (the primary cause of HCI degradation) are only concentrated in a few parts of the circuit, severely degrading some portions more than others. Our techniques increase the lifetime of an NoC router by balancing this switching activity. Compared to an NoC without any reliability techniques, our best schemes improve the switching activity distribution, clock cycle degradation, system performance and energy delay product per flit by 19%, 26%, 11% and 17%, respectively, on an average.

Aggressive technology scaling has led Integrated Circuits (ICs) suffer from ever-increasing wearout effects. As a consequence, Dynamic Reliability Management (DRM) becomes an essential approach to assure IC's lifetime reliability. Accurate and efficient reliability modeling from low-level aging sensor measurements is critical to DRM systems. This work presents a Time-Sharing Sensing (TSS) method for $V_{th}$-sensor based DRM to assess the dynamic NBTI-induced degradation experienced by the circuit under monitoring. SPICE simulation results suggest that the proposed TSS method can accurately capture the circuit reliability status under random stress conditions.

In the period of extreme CMOS scaling, reliability issues are becoming a critical problem. These problems include issues related to device reliability, in the form of bias temperature instability, hot carrier injection, time-dependent dielectric breakdown of gate oxides, as well as interconnect reliability concerns such as electromigration and TSV stress in 3D integrated circuits. This tutorial surveys these effects, and discusses methods for mitigating them at all levels of design.

As device sizes shrink, device-level manufacturing challenges have led to increased variability in physical circuit characteristics. Exponentially increasing circuit density has not only brought about concerns in the reliable manufacturing of circuits, but has also exaggerated variations in dynamic circuit behavior. The resulting uncertainty in performance, power, and reliability imposed by compounding static and dynamic non-determinism threatens to halt the continuation of Moore's law, which has been arguably the primary driving force behind technology and innovation for decades. As the marginal benefits of technology scaling continue to languish, a new vision for stochastic computing has begun to emerge. Rather than hiding variations under expensive guardbands, designers have begun to relax traditional correctness constraints and deliberately expose hardware variability to higher levels of the compute stack, thus tapping into potentially significant performance and energy benefits, while exploiting software and hardware error resilience to tolerate errors. In this paper, we present our vision for design, architecture, compiler, and application-level stochastic computing techniques that embrace errors in order to ensure the continued viability of semiconductor scaling.

We formulate the problem of energy consumption and reliability oriented application mapping on regular Network-on-Chip topologies. We propose a novel branch-and-bound based algorithm to solve this problem. Reliability is estimated by an efficient Monte Carlo algorithm based on the destruction spectrum of the network. Simulation results demonstrate that reliability can be improved without sacrificing much of energy consumption.

Variations in power supply voltage, which is a function of the power delivery network and dynamic current consumption, can affect circuit reliability. Much work has been done to understand power delivery robustness during both the design phase as well as the post-silicon validation phase. Methods applicable at the design phase typically synthesize worst-case current waveforms based on simple current constraints but fail to provide corresponding instruction streams due to their ignorance of the functional aspects of the machine and hence cannot be validated. Approaches used for post-silicon validation are not useful during design, and either rely heavily on available test content which can come from power, performance, or defect testing, and hence are limited in validation potential or employ manually-crafted tests aimed at power delivery, and hence are highly labor-intensive. In this paper, we provide a novel approach to construct processor current waveforms to induce significant droops while at the same time producing instruction streams to achieve those waveforms. We solve the pre-silicon current stimulus generation problem as an optimization problem. The modular framework in this paper utilizes microarchitectural information, current consumption estimates of fine-grained microarchitectural components and a pre-characterized power delivery network to obtain significant droop-inducing current waveforms. The paper further discusses techniques to convert operations associated with these generated waveforms to functional instruction streams. Silicon measurements of such tests run on an industrial microprocessor validate the approach.

Voltage scaling is one of the most effective mechanisms to reduce microprocessor power consumption. However, the increased severity of manufacturing-induced parameter variations at lower voltages limits voltage scaling to a minimum voltage, Vccmin, below which a processor cannot operate reliably. Memory cell failures in large memory structures (e.g., caches) typically determine the Vccmin for the whole processor. Memory failures can be persistent (i.e., failures at time zero which cause yield loss) or non-persistent (e.g., soft errors or erratic bit failures). Both types of failures increase as supply voltage decreases and both need to be addressed to achieve reliable operation at low voltages. In this paper, we propose a novel adaptive technique to improve cache lifetime reliability and enable low voltage operation. This technique, multi-bit segmented ECC (MS-ECC) addresses both persistent and non-persistent failures. Like previous work on mitigating persistent failures, MS-ECC trades off cache capacity for lower voltages. However, unlike previous schemes, MS-ECC does not rely on testing to identify and isolate defective bits, and therefore enables error tolerance for non-persistent failures like erratic bits and soft errors at low voltages. Furthermore, MS-ECC's design can allow the operating system to adaptively change the cache size and ECC capability to adjust to system operating conditions. Compared to current designs with single-bit correction, the most aggressive implementation for MS-ECC enables a 30% reduction in supply voltage, reducing power by 71% and energy per instruction by 42%.

Voltage and frequency margins necessary to ensure correct processor operation under dynamic voltage, temperature, and aging variations result in performance and power overheads. Resilient circuit techniques, including embedded error-detection sequentials and tunable replica circuits, allow these margins to be reduced or eliminated, resulting in reliable, energy-efficient operation. Categories and Subject Descriptors B.7.1 [Integrated Circuits]: Types and design styles General Terms Performance, Design, Reliability

Circuit reliability is affected by various fabrication-time and run-time effects. Fabrication-induced process variation has significant impact on circuit performance and reliability. Various aging effects, such as negative bias temperature instability, cause continuous performance and reliability degradation during circuit run-time usage. In this work, we present a statistical analysis framework that characterizes the lifetime reliability of nanometer-scale integrated circuits by jointly considering the impact of fabrication-induced process variation and run-time aging effects. More specifically, our work focuses on characterizing circuit threshold voltage lifetime variation and its impact on circuit timing due to process variation and the negative bias temperature instability effect, a primary aging effect in nanometer-scale integrated circuits. The proposed work is capable of characterizing the overall circuit lifetime reliability, as well as efficiently quantifying the vulnerabilities of individual circuit elements. This analysis framework has been carefully validated and integrated into an iterative design flow for circuit lifetime reliability analysis and optimization.

State elements are increasingly vulnerable to soft errors due to their decreasing size, and the fact that latched errors cannot be completely eliminated by electrical or timing masking. Most prior methods of reducing the soft-error rate (SER) involve combinational redesign, which tends to add area and decrease testability, the latter a concern due to the prevalence of manufacturing defects. Our work explores the fundamental relations between the SER of sequential circuits and their testability in scan mode, and appears to be the first to improve both through retiming. Our retiming methodology relocates registers so that 1) registers become less observable with respect to primary outputs, thereby decreasing overall SER, and 2) combinational nodes become more observable with respect to registers (but not with respect to primary outputs), thereby increasing scan-testability. We present experimental results which show an average decrease of 42% in the SER of latches, and an average improvement of 31% random-pattern testability.

Power constrained designs are becoming increasingly sensitive to supply voltage noise. We propose a hardware-software collaborative approach to enable aggressive operating margins: a checkpoint-recovery mechanism corrects margin violations, while a run-time software layer reschedules the program's instruction stream to prevent recurring margin crossings at the same program location. The run-time layer removes 60% of these events with minimal overhead, thereby significantly improving overall performance.

In this work we propose an online reliability tracking framework that utilizes a hybrid network of on-chip temperature and delay sensors together with a circuit reliability macromodel. We are concerned specifically with NBTI-induced transistor aging, which manifests itself as the gradual increase of PMOS threshold voltage and increase of circuit delay over time. The key feature of our work is an explicit macromodel which maps operating temperature to circuit degradation. The macromodel allows for cost-effective reliability tracking. The accuracy of the model is improved by online calibration of model parameters via monitoring the delay degradation of ring oscillators. The number of model parameters is relatively small. For example, in ISCAS'85 benchmark circuits, at most 21 parameters are required for the macromodel. The prediction of circuit degradation using our online monitoring strategy can be up to 20% less conservative compared to the worst-case reliability prediction.

We present a low-overhead solution to tackle the delay increase caused by Negative Bias Temperature Instability (NBTI), which has emerged as the most critical reliability issue in sub-90nm technology nodes.The proposed solution consists of using special type of registers, called soft-edge flip-flops (SEFFs), which allow to compensate for the delay increase by introducing a transparency window. SEFFs are an effective alternative to existing solutions such as threshold, supply, or body-bias voltage modulation, since they provide minimum area and power overhead, and can seamlessly replace regular FFs.Results show that delay degradation up-to 60ps after 10 years of aging can be accounted for with a very small (less than 1%) area penalty.

Soft errors, once only of concern in memories, are beginning to affect logic as well. Determining the soft error rate (SER) of a combinational circuit involves three main masking mechanisms: logic, timing and electrical. Most previous papers focus on logic and electrical masking. Here, we develop static and statistical analysis techniques to estimate timing masking through the error-latching window of each gate. Our SER analysis algorithms incorporating timing masking are 10 - 100x faster than comparable evaluators and can be used in synthesis and layout. We show that 62% of gates identified as error-critical using timing masking would not be identifiable by considering only logic masking. Furthermore, hardening the top 10% of error-critical gates leads to a 43% reduction in the SER. We also propose to decrease the error-latching window of each gate by relocating it such that path lengths to primary outputs are equalized. Our results show that this technique yields 14% improvement in SER with no area overhead.

With the scaling down of the CMOS technologies, Negative Bias Temperature Instability (NBTI) has become a major concern due to its impact on PMOS transistor aging process and the corresponding reduction in the long-term reliability of CMOS circuits. This paper investigates the effect of NBTI phenomenon on the setup and hold times of flip-flops. First, it is shown that NBTI tightens the setup and hold timing constraints imposed on the flip-flops in the design. Second, different types of flip-flops exhibit different levels of susceptibility to NBTI-induced change in their setup/hold time values. Finally, an NBTI-aware transistor sizing technique can minimize the NBTI effect on timing characteristics of the flip-flops.

In recent years, due to rapid advances in VLSI manufacturing technology capable of packing more and more devices and wires on a chip, crosstalk has emerged as a serious problem affecting circuit reliability. Even though FPGAs are more immune to crosstalk noise than their ASIC counterparts manufactured in the same technological process, we have reached the point where FPGAs have become affected by crosstalk as well. Because FPGAs have regular interconnect structures, crosstalk noise can be more easily controlled. In this paper, we investigate the crosstalk noise in FPGAs and propose new strategies to reduce its impact on delay. Our methods can reduce crosstalk noise by statistically significant amounts with no penalty in performance, power, or area.

Recent studies show that the nonuniform thermal distribution on the substrate and interconnects has impact on the circuit reliability and performance. Hence three-dimensional (3-D) thermal analysis is crucial to analyze these effects. In this paper, we present and develop an efficient 3-D transient thermal simulator based on the alternating direction implicit (ADI) method for large scale temperature estimation problems. Our simulator, 3D Thermal-ADI, not only has a linear runtime and memory requirement, but also is unconditionally stable. Detailed analysis of the 3-D nonhomogeneous cases and boundary conditions for on-chip VLSI applications are introduced and presented. Extensive experimental results show that our algorithm is not only orders of magnitude faster than the traditional thermal simulation algorithms, but is also highly accurate and memory efficient. The temperature profile of steady state can be reached in few iterations. The software is avaiable on the web [1].