Natasa Miskov-Zivanov

Circuit Reliability Analysis Using Symbolic Techniques

Due to the shrinking of feature size and the significant reduction in noise margins, nanoscale circuits have become more susceptible to manufacturing defects, noise-related transient faults, and interference from radiation. Traditionally, soft errors have been a much greater concern in memories than in logic circuits. However, as technology continues to scale, logic circuits are becoming more susceptible to soft errors than memories. To estimate the susceptibility to errors in combinational logic, the use of binary decision diagrams (BDDs) and algebraic decision diagrams (ADDs) for the unified symbolic analysis of circuit reliability is proposed. A framework that uses BDDs and ADDs and enables the analysis of combinational circuit reliability from different aspects, e.g., output susceptibility to error, influence of individual gates on individual outputs and overall circuit reliability, and the dependence of circuit reliability on glitch duration, amplitude, and input patterns, is presented. This is demonstrated by the set of experimental results, which show that the mean output error susceptibility can vary from less then 0.1% for large circuits and short glitches (20% cycle time) to about 30% for very small circuits and long enough glitches (50% cycle time)

Multiple Transient Faults in Combinational and Sequential Circuits: A Systematic Approach

Transient faults in logic circuits are becoming an important reliability concern for future technology nodes. Radiation-induced faults have received significant attention in recent years, while multiple transients originating from a single radiation hit are predicted to occur more often. Furthermore, some effects, like reconvergent fanout-induced glitches, are more pronounced in the case of multiple faults. Therefore, to guide the design process and the choice of circuit optimization techniques, it is important to model multiple faults and their propagation through logic circuits, while evaluating the changes in error rates resulting from multiple simultaneous faults. In this paper, we show how output error probabilities change with increasing number of simultaneous faults and we also analyze the impact of multiple errors in state flip-flops, during the cycles following the cycle when fault(s) occurred. The results obtained using the proposed framework show that output error probability resulting from multiple-event transient or multiple-bit upsets can vary across different outputs and different circuits by several orders of magnitude. The results also show that the impact of different masking factors also varies across circuits and this information can be valuable for customizing protection techniques.

The Duration of T Cell Stimulation Is a Critical Determinant of Cell Fate and Plasticity

The duration of T cell receptor contact with antigen modulates the pattern of downstream signaling to determine CD4+ T cell fate. Signal Duration Controls T Cell Fate CD4+ T cells are broadly classified into two groups: T helper (TH) cells, which mediate the immune response, and regulatory T (Treg) cells, which suppress immunity. Both cell types can arise from the differentiation of naïve CD4+ T cells stimulated through the T cell receptor (TCR) by antigen. Cell fate is thought to arise from differences in the intensity of the TCR signal, with strong TCR signals generating TH cells and weaker TCR signals generating Treg cells. Understanding how to manipulate T cell fate has implications for immunotherapies; for example, generating too few Treg cells can lead to autoimmunity, whereas generating too many Treg cells can suppress antitumor immunity. Miskov-Zivanov et al. developed a logical mathematical model of T cell differentiation focused on early stages of TCR signaling and found that differential activation of TCR signaling pathways by low and high doses of antigen was better modeled as changes in the duration, rather than the intensity, of TCR signaling. Their model predicted, and experiments confirmed, that there is a time window for signaling during which T cell fate is plastic and that varying the duration of stimulation controls the relative proportion of Treg and TH cells produced. The model also predicts that the TH cell phenotype stabilized more rapidly than did the Treg cell phenotype. Together, these data suggest that differential timing of TCR signaling events plays an important role in determining T cell fate. Variations in T cell receptor (TCR) signal strength, as indicated by differential activation of downstream signaling pathways, determine the fate of naïve T cells after encounter with antigen. Low-strength signals favor differentiation into regulatory T (Treg) cells containing the transcription factor Foxp3, whereas high-strength signals favor generation of interleukin-2–producing T helper (TH) cells. We constructed a logic circuit model of TCR signaling pathways, a major feature of which is an incoherent feed-forward loop involving both TCR-dependent activation of Foxp3 and its inhibition by mammalian target of rapamycin (mTOR), leading to the transient appearance of Foxp3+ cells under TH cell–generating conditions. Experiments confirmed this behavior and the prediction that the immunosuppressive cytokine TGF-β (transforming growth factor–β) could generate Treg cells even during continued Akt-mTOR signaling. We predicted that sustained mTOR activity could suppress FOXP3 expression upon TGF-β removal, suggesting a possible mechanism for the experimentally observed instability of Foxp3+ cells. Our model predicted, and experiments confirmed, that transient stimulation of cells with high-dose antigen generated TH, Treg, and nonactivated cells in proportions depending on the duration of TCR stimulation. Experimental analysis of cells after antigen removal identified three populations that correlated with these T cell fates. Further analysis of simulations implicated a negative feedback loop involving Foxp3, the phosphatase PTEN, and Akt-mTOR in determining fate. These results suggest that there is a critical time after TCR stimulation during which heterogeneity in the differentiating population of cells leads to increased plasticity of cell fate.

Soft error rate analysis for sequential circuits

Due to reduction in device feature size and supply voltage, the sensitivity to radiation induced transient faults (soft errors) of digital systems increases dramatically. Intensive research has been done so far in modeling and analysis of combinational circuit susceptibility to soft errors, while sequential circuits have received much less attention. In this paper, we present an approach for evaluating the susceptibility of sequential circuits to soft errors. The proposed approach uses symbolic modeling based on BDDs/ADDs and probabilistic sequential circuit analysis. The SER evaluation is demonstrated by the set of experimental results, which show that, for most of the benchmarks used, the SER decreases well below a given threshold (10-7 FIT) within ten clock cycles after the hit. The results obtained with the proposed symbolic framework are within 4% average error and up to 11000X faster when compared to HSPICE detailed circuit simulation.

A systematic approach to modeling and analysis of transient faults in logic circuits

With technology scaling, the occurrence rate of not only single, but also multiple transients resulting from a single hit is increasing. In this work, we consider the effect of these multiple-event transients on the outputs of logic circuits. Our framework allows for the analysis of soft errors in logic circuits, including several aspects: estimation of the effect of both single and multiple transient faults on both combinational and sequential circuits, analysis of the impact of multiple flip-flop upsets in sequential circuits, and analysis of transient behavior of the soft error rate in the cycles following the hit. The proposed framework can be used to estimate the impact of transient faults stemming not only from radiation, but also other physical phenomena. The results obtained using the proposed framework show that output error rates, resulting from multiple-event transient or multiple-bit upsets can vary across different circuits by several orders of magnitude.

Cutting Edge: Differential Regulation of PTEN by TCR, Akt, and FoxO1 Controls CD4+ T Cell Fate Decisions

Signaling via the Akt/mammalian target of rapamycin pathway influences CD4+ T cell differentiation; low levels favor regulatory T cell induction and high levels favor Th induction. Although the lipid phosphatase phosphatase and tensin homolog (PTEN) suppresses Akt activity, the control of PTEN activity is poorly studied in T cells. In this study, we identify multiple mechanisms that regulate PTEN expression. During Th induction, PTEN function is suppressed via lower mRNA levels, lower protein levels, and an increase in C-terminal phosphorylation. Conversely, during regulatory T cell induction, PTEN function is maintained through the stabilization of PTEN mRNA transcription and sustained protein levels. We demonstrate that differential Akt/mammalian target of rapamycin signaling regulates PTEN transcription via the FoxO1 transcription factor. A mathematical model that includes multiple modes of PTEN regulation recapitulates our experimental findings and demonstrates how several feedback loops determine differentiation outcomes. Collectively, this work provides novel mechanistic insights into how differential regulation of PTEN controls alternate CD4+ T cell fate outcomes.

Studies of biological networks with statistical model checking: application to immune system cells

We use computational modeling and formal analysis techniques to study temporal behavior of a discrete logical model of the naïve T cell differentiation. The model is analyzed formally and automatically by performing temporal logic queries via statistical model checking. The results obtained using model checking provide details about relative timing of events in the system, which would otherwise be very cumbersome and time consuming to obtain through simulations only.

Formal modeling and reasoning for reliability analysis

Transient faults in logic circuits are an important reliability concern for future technology nodes. In order to guide the design process and the choice of circuit optimization techniques, it is important to accurately and efficiently model transient faults and their propagation through logic circuits, while evaluating the error rates resulting from transient faults. To this end, we give an overview of the existing formal methods for modeling and reasoning about transient faults. We describe the main aspects of transient fault propagation and the advantages and drawbacks of different approaches to modeling them.

Emulation of biological networks in reconfigurable hardware

Models of biological networks have been studied through simulations using a number of software tools. However, the intrinsic disparity between the sequential nature of microprocessor architecture used in software-based simulations and the highly parallel nature of biological systems may result in prohibitively long simulation times. In this work, we adopt an alternative approach to simulation of biological systems using hardware-based emulation. Our results on Boolean network models show that such an approach can provide speedup of 17,000X when compared to existing software simulation approaches.

Dynamic behavior of cell signaling networks: model design and analysis automation

Recent work has presented logical models and showed the benefits of applying logical approaches to studying the dynamics of biological networks. In this work, we develop a methodology for automating the design of such models by utilizing methods and algorithms from the field of electronic design automation. We anticipate that automated discrete model development will greatly improve the efficiency of qualitative analysis of biological networks.