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IC design for reliability
textAs the feature size of integrated circuits goes down to the nanometer scale,
transient and permanent reliability issues are becoming a significant concern for circuit
designers. Traditionally, the reliability issues were mostly handled at the device level as a
device engineering problem. However, the increasing severity of reliability challenges
and higher error rates due to transient upsets favor higher-level design for reliability
(DFR). In this work, we develop several methods for DFR at the circuit level.
A major source of transient errors is the single event upset (SEU). SEUs are
caused by high-energy particles present in the cosmic rays or emitted by radioactive
contaminants in the chip packaging materials. When these particles hit a N+/P+ depletion
region of an MOS transistor, they may generate a temporary logic fault. Depending on
where the MOS transistor is located and what state the circuit is at, an SEU may result in
a circuit-level error. We analyze SEUs both in combinational logic and memories
(SRAM). For combinational logic circuit, we propose FASER, a Fast Analysis tool of
Soft ERror susceptibility for cell-based designs. The efficiency of FASER is achieved
through its static and vector-less nature. In order to evaluate the impact of SEU on SRAM, a theory for estimating dynamic noise margins is developed analytically. The
results allow predicting the transient error susceptibility of an SRAM cell using a closedform
expression.
Among the many permanent failure mechanisms that include time-dependent
oxide breakdown (TDDB), electro-migration (EM), hot carrier effect (HCE), and
negative bias temperature instability (NBTI), NBTI has recently become important.
Therefore, the main focus of our work is NBTI. NBTI occurs when the gate of PMOS is
negatively biased. The voltage stress across the gate generates interface traps, which
degrade the threshold voltage of PMOS. The degraded PMOS may eventually fail to meet
timing requirement and cause functional errors. NBTI becomes severe at elevated
temperatures. In this dissertation, we propose a NBTI degradation model that takes into
account the temperature variation on the chip and gives the accurate estimation of the
degraded threshold voltage.
In order to account for the degradation of devices, traditional design methods add
guard-bands to ensure that the circuit will function properly during its lifetime. However,
the worst-case based guard-bands lead to significant penalty in performance. In this
dissertation, we propose an effective macromodel-based reliability tracking and
management framework, based on a hybrid network of on-chip sensors, consisting of
temperature sensors and ring oscillators. The model is concerned specifically with NBTIinduced
transistor aging. The key feature of our work, in contrast to the traditional
tracking techniques that rely solely on direct measurement of the increase of threshold
voltage or circuit delay, is an explicit macromodel which maps operating temperature to
circuit degradation (the increase of circuit delay). The macromodel allows for costeffective
tracking of reliability using temperature sensors and is also essential for
enabling the control loop of the reliability management system. The developed methods improve the over-conservatism of the device-level, worstcase
reliability estimation techniques. As the severity of reliability challenges continue to
grow with technology scaling, it will become more important for circuit designers/CAD
tools to be equipped with the developed methods.Electrical and Computer Engineerin
Reliability-energy-performance optimisation in combinational circuits in presence of soft errors
PhD ThesisThe reliability metric has a direct relationship to the amount of value produced
by a circuit, similar to the performance metric. With advances in CMOS
technology, digital circuits become increasingly more susceptible to soft errors.
Therefore, it is imperative to be able to assess and improve the level of reliability
of these circuits. A framework for evaluating and improving the reliability of
combinational circuits is proposed, and an interplay between the metrics of
reliability, energy and performance is explored.
Reliability evaluation is divided into two levels of characterisation: stochastic
fault model (SFM) of the component library and a design-specific critical vector
model (CVM). The SFM captures the properties of components with regard to
the interference which causes error. The CVM is derived from a limited number
of simulation runs on the specific design at the design time and producing
the reliability metric. The idea is to move the high-complexity problem of the
stochastic characterisation of components to the generic part of the design
process, and to do it just once for a large number of specific designs. The
method is demonstrated on a range of circuits with various structures.
A three-way trade-off between reliability, energy, and performance has
been discovered; this trade-off facilitates optimisations of circuits and their
operating conditions.
A technique for improving the reliability of a circuit is proposed, based on
adding a slow stage at the primary output. Slow stages have the ability to
absorb narrow glitches from prior stages, thus reducing the error probability.
Such stages, or filters, suppress most of the glitches generated in prior stages
and prevent them from arriving at the primary output of the circuit. Two filter
solutions have been developed and analysed. The results show a dramatic
improvement in reliability at the expense of minor performance and energy
penalties.
To alleviate the problem of the time-consuming analogue simulations involved in the proposed method, a simplification technique is proposed. This
technique exploits the equivalence between the properties of the gates within
a path and the equivalence between paths. On the basis of these equivalences,
it is possible to reduce the number of simulation runs. The effectiveness of
the proposed technique is evaluated by applying it to different circuits with
a representative variety of path topologies. The results show a significant
decrease in the time taken to estimate reliability at the expense of a minor
decrease in the accuracy of estimation. The simplification technique enables
the use of the proposed method in applications with complex circuits.Ministry of Education and Scientific Research in Liby
Fast and accurate SER estimation for large combinational blocks in early stages of the design
Soft Error Rate (SER) estimation is an important challenge for integrated circuits because of the increased vulnerability brought by technology scaling. This paper presents a methodology to estimate in early stages of the design the susceptibility of combinational circuits to particle strikes. In the core of the framework lies MASkIt , a novel approach that combines signal probabilities with technology characterization to swiftly compute the logical, electrical, and timing masking effects of the circuit under study taking into account all input combinations and pulse widths at once. Signal probabilities are estimated applying a new hybrid approach that integrates heuristics along with selective simulation of reconvergent subnetworks. The experimental results validate our proposed technique, showing a speedup of two orders of magnitude in comparison with traditional fault injection estimation with an average estimation error of 5 percent. Finally, we analyze the vulnerability of the Decoder, Scheduler, ALU, and FPU of an out-of-order, superscalar processor design.This work has been partially supported by the Spanish Ministry of Economy and Competitiveness and Feder Funds under grant TIN2013-44375-R, by the Generalitat de Catalunya under grant FI-DGR 2016, and by the FP7 program of the EU under contract FP7-611404 (CLERECO).Peer ReviewedPostprint (author's final draft
Custom Integrated Circuits
Contains reports on nine research projects.Analog Devices, Inc.International Business Machines CorporationJoint Services Electronics Program Contract DAAL03-89-C-0001U.S. Air Force - Office of Scientific Research Contract AFOSR 86-0164BDuPont CorporationNational Science Foundation Grant MIP 88-14612U.S. Navy - Office of Naval Research Contract N00014-87-K-0825American Telephone and TelegraphDigital Equipment CorporationNational Science Foundation Grant MIP 88-5876
Error Mitigation Using Approximate Logic Circuits: A Comparison of Probabilistic and Evolutionary Approaches
Technology scaling poses an increasing challenge to the reliability of digital circuits. Hardware redundancy solutions, such as triple modular redundancy (TMR), produce very high area overhead, so partial redundancy is often used to reduce the overheads. Approximate logic circuits provide a general framework for optimized mitigation of errors arising from a broad class of failure mechanisms, including transient, intermittent, and permanent failures. However, generating an optimal redundant logic circuit that is able to mask the faults with the highest probability while minimizing the area overheads is a challenging problem. In this study, we propose and compare two new approaches to generate approximate logic circuits to be used in a TMR schema. The probabilistic approach approximates a circuit in a greedy manner based on a probabilistic estimation of the error. The evolutionary approach can provide radically different solutions that are hard to reach by other methods. By combining these two approaches, the solution space can be explored in depth. Experimental results demonstrate that the evolutionary approach can produce better solutions, but the probabilistic approach is close. On the other hand, these approaches provide much better scalability than other existing partial redundancy techniques.This work was supported by the Ministry of Economy and Competitiveness of Spain under project ESP2015-68245-C4-1-P, and by the Czech science foundation project GA16-17538S and the Ministry of Education, Youth and Sports of the Czech Republic from the National Programme of Sustainability (NPU II); project IT4Innovations excellence in science - LQ1602
Power Estimation Technique for DSP Architectures.
The main goal of power estimation is to optimize the power consumption of a electronic design. Power is a strongly pattern dependent function. Input statistics greatly influence on average power. We solve the pattern dependence problem for intellectual property (IP) designs. In this paper, we present a power macro-modeling technique for digital signal processing (DSP) architectures in terms of the statistical knowledge of their primary inputs. During the power estimation procedure, the sequence of an input stream is generated by a genetic algorithm using input metrics. Then, a Monte Carlo zero delay simulation is performed and a power dissipation macro-model function is built from power dissipation results. From then on, this macro-model function can be used to estimate power dissipation of the system just by using the statistics of the macro-block’s primary in puts. In experiments with the DSP system, the average error is 26%
Custom Integrated Circuits
Contains reports on twelve research projects.Analog Devices, Inc.International Business Machines, Inc.Joint Services Electronics Program (Contract DAAL03-86-K-0002)Joint Services Electronics Program (Contract DAAL03-89-C-0001)U.S. Air Force - Office of Scientific Research (Grant AFOSR 86-0164)Rockwell International CorporationOKI Semiconductor, Inc.U.S. Navy - Office of Naval Research (Contract N00014-81-K-0742)Charles Stark Draper LaboratoryNational Science Foundation (Grant MIP 84-07285)National Science Foundation (Grant MIP 87-14969)Battelle LaboratoriesNational Science Foundation (Grant MIP 88-14612)DuPont CorporationDefense Advanced Research Projects Agency/U.S. Navy - Office of Naval Research (Contract N00014-87-K-0825)American Telephone and TelegraphDigital Equipment CorporationNational Science Foundation (Grant MIP-88-58764
Cross-layer Soft Error Analysis and Mitigation at Nanoscale Technologies
This thesis addresses the challenge of soft error modeling and mitigation in nansoscale technology nodes and pushes the state-of-the-art forward by proposing novel modeling, analyze and mitigation techniques. The proposed soft error sensitivity analysis platform accurately models both error generation and propagation starting from a technology dependent device level simulations all the way to workload dependent application level analysis
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