Matching Items (7)
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- All Subjects: Reliability
- Creators: Clark, Lawrence
- Creators: Schroder, Dieter
Description
Memories play an integral role in today's advanced ICs. Technology scaling has enabled high density designs at the price paid for impact due to variability and reliability. It is imperative to have accurate methods to measure and extract the variability in the SRAM cell to produce accurate reliability projections for future technologies. This work presents a novel test measurement and extraction technique which is non-invasive to the actual operation of the SRAM memory array. The salient features of this work include i) A single ended SRAM test structure with no disturbance to SRAM operations ii) a convenient test procedure that only requires quasi-static control of external voltages iii) non-iterative method that extracts the VTH variation of each transistor from eight independent switch point measurements. With the present day technology scaling, in addition to the variability with the process, there is also the impact of other aging mechanisms which become dominant. The various aging mechanisms like Negative Bias Temperature Instability (NBTI), Channel Hot Carrier (CHC) and Time Dependent Dielectric Breakdown (TDDB) are critical in the present day nano-scale technology nodes. In this work, we focus on the impact of NBTI due to aging in the SRAM cell and have used Trapping/De-Trapping theory based log(t) model to explain the shift in threshold voltage VTH. The aging section focuses on the following i) Impact of Statistical aging in PMOS device due to NBTI dominates the temporal shift of SRAM cell ii) Besides static variations , shifting in VTH demands increased guard-banding margins in design stage iii) Aging statistics remain constant during the shift, presenting a secondary effect in aging prediction. iv) We have investigated to see if the aging mechanism can be used as a compensation technique to reduce mismatch due to process variations. Finally, the entire test setup has been tested in SPICE and also validated with silicon and the results are presented. The method also facilitates the study of design metrics such as static, read and write noise margins and also the data retention voltage and thus help designers to improve the cell stability of SRAM.
ContributorsRavi, Venkatesa (Author) / Cao, Yu (Thesis advisor) / Bakkaloglu, Bertan (Committee member) / Clark, Lawrence (Committee member) / Arizona State University (Publisher)
Created2013
Description
Electromigration in metal interconnects is the most pernicious failure mechanism in semiconductor integrated circuits (ICs). Early electromigration investigations were primarily focused on aluminum interconnects for silicon-based ICs. An alternative metallization compatible with gallium arsenide (GaAs) was required in the development of high-powered radio frequency (RF) compound semiconductor devices operating at higher current densities and elevated temperatures. Gold-based metallization was implemented on GaAs devices because it uniquely forms a very low resistance ohmic contact and gold interconnects have superior electrical and thermal conductivity properties. Gold (Au) was also believed to have improved resistance to electromigration due to its higher melting temperature, yet electromigration reliability data on passivated Au interconnects is scarce and inadequate in the literature. Therefore, the objective of this research was to characterize the electromigration lifetimes of passivated Au interconnects under precisely controlled stress conditions with statistically relevant quantities to obtain accurate model parameters essential for extrapolation to normal operational conditions. This research objective was accomplished through measurement of electromigration lifetimes of large quantities of passivated electroplated Au interconnects utilizing high-resolution in-situ resistance monitoring equipment. Application of moderate accelerated stress conditions with a current density limited to 2 MA/cm2 and oven temperatures in the range of 300°C to 375°C avoided electrical overstress and severe Joule-heated temperature gradients. Temperature coefficients of resistance (TCRs) were measured to determine accurate Joule-heated Au interconnect film temperatures. A failure criterion of 50% resistance degradation was selected to prevent thermal runaway and catastrophic metal ruptures that are problematic of open circuit failure tests. Test structure design was optimized to reduce resistance variation and facilitate failure analysis. Characterization of the Au microstructure yielded a median grain size of 0.91 ìm. All Au lifetime distributions followed log-normal distributions and Black's model was found to be applicable. An activation energy of 0.80 ± 0.05 eV was measured from constant current electromigration tests at multiple temperatures. A current density exponent of 1.91 was extracted from multiple current densities at a constant temperature. Electromigration-induced void morphology along with these model parameters indicated grain boundary diffusion is dominant and the void nucleation mechanism controlled the failure time.
ContributorsKilgore, Stephen (Author) / Adams, James (Thesis advisor) / Schroder, Dieter (Thesis advisor) / Krause, Stephen (Committee member) / Gaw, Craig (Committee member) / Arizona State University (Publisher)
Created2013
Description
Thanks to continuous technology scaling, intelligent, fast and smaller digital systems are now available at affordable costs. As a result, digital systems have found use in a wide range of application areas that were not even imagined before, including medical (e.g., MRI, remote or post-operative monitoring devices, etc.), automotive (e.g., adaptive cruise control, anti-lock brakes, etc.), security systems (e.g., residential security gateways, surveillance devices, etc.), and in- and out-of-body sensing (e.g., capsule swallowed by patients measuring digestive system pH, heart monitors, etc.). Such computing systems, which are completely embedded within the application, are called embedded systems, as opposed to general purpose computing systems. In the design of such embedded systems, power consumption and reliability are indispensable system requirements. In battery operated portable devices, the battery is the single largest factor contributing to device cost, weight, recharging time, frequency and ultimately its usability. For example, in the Apple iPhone 4 smart-phone, the battery is $40\%$ of the device weight, occupies $36\%$ of its volume and allows only $7$ hours (over 3G) of talk time. As embedded systems find use in a range of sensitive applications, from bio-medical applications to safety and security systems, the reliability of the computations performed becomes a crucial factor. At our current technology-node, portable embedded systems are prone to expect failures due to soft errors at the rate of once-per-year; but with aggressive technology scaling, the rate is predicted to increase exponentially to once-per-hour. Over the years, researchers have been successful in developing techniques, implemented at different layers of the design-spectrum, to improve system power efficiency and reliability. Among the layers of design abstraction, I observe that the interface between the compiler and processor micro-architecture possesses a unique potential for efficient design optimizations. A compiler designer is able to observe and analyze the application software at a finer granularity; while the processor architect analyzes the system output (power, performance, etc.) for each executed instruction. At the compiler micro-architecture interface, if the system knowledge at the two design layers can be integrated, design optimizations at the two layers can be modified to efficiently utilize available resources and thereby achieve appreciable system-level benefits. To this effect, the thesis statement is that, ``by merging system design information at the compiler and micro-architecture design layers, smart compilers can be developed, that achieve reliable and power-efficient embedded computing through: i) Pure compiler techniques, ii) Hybrid compiler micro-architecture techniques, and iii) Compiler-aware architectures''. In this dissertation demonstrates, through contributions in each of the three compiler-based techniques, the effectiveness of smart compilers in achieving power-efficiency and reliability in embedded systems.
ContributorsJeyapaul, Reiley (Author) / Shrivastava, Aviral (Thesis advisor) / Vrudhula, Sarma (Committee member) / Clark, Lawrence (Committee member) / Colbourn, Charles (Committee member) / Arizona State University (Publisher)
Created2012
Description
This dissertation addresses challenges pertaining to multi-junction (MJ) solar cells from material development to device design and characterization. Firstly, among the various methods to improve the energy conversion efficiency of MJ solar cells using, a novel approach proposed recently is to use II-VI (MgZnCd)(SeTe) and III-V (AlGaIn)(AsSb) semiconductors lattice-matched on GaSb or InAs substrates for current-matched subcells with minimal defect densities. CdSe/CdTe superlattices are proposed as a potential candidate for a subcell in the MJ solar cell designs using this material system, and therefore the material properties of the superlattices are studied. The high structural qualities of the superlattices are obtained from high resolution X-ray diffraction measurements and cross-sectional transmission electron microscopy images. The effective bandgap energies of the superlattices obtained from the photoluminescence (PL) measurements vary with the layer thicknesses, and are smaller than the bandgap energies of either the constituent material. Furthermore, The PL peak position measured at the steady state exhibits a blue shift that increases with the excess carrier concentration. These results confirm a strong type-II band edge alignment between CdSe and CdTe. The valence band offset between unstrained CdSe and CdTe is determined as 0.63 eV±0.06 eV by fitting the measured PL peak positions using the Kronig-Penney model. The blue shift in PL peak position is found to be primarily caused by the band bending effect based on self-consistent solutions of the Schrödinger and Poisson equations. Secondly, the design of the contact grid layout is studied to maximize the power output and energy conversion efficiency for concentrator solar cells. Because the conventional minimum power loss method used for the contact design is not accurate in determining the series resistance loss, a method of using a distributed series resistance model to maximize the power output is proposed for the contact design. It is found that the junction recombination loss in addition to the series resistance loss and shadowing loss can significantly affect the contact layout. The optimal finger spacing and maximum efficiency calculated by the two methods are close, and the differences are dependent on the series resistance and saturation currents of solar cells. Lastly, the accurate measurements of external quantum efficiency (EQE) are important for the design and development of MJ solar cells. However, the electrical and optical couplings between the subcells have caused EQE measurement artifacts. In order to interpret the measurement artifacts, DC and small signal models are built for the bias condition and the scan of chopped monochromatic light in the EQE measurements. Characterization methods are developed for the device parameters used in the models. The EQE measurement artifacts are found to be caused by the shunt and luminescence coupling effects, and can be minimized using proper voltage and light biases. Novel measurement methods using a pulse voltage bias or a pulse light bias are invented to eliminate the EQE measurement artifacts. These measurement methods are nondestructive and easy to implement. The pulse voltage bias or pulse light bias is superimposed on the conventional DC voltage and light biases, in order to control the operating points of the subcells and counterbalance the effects of shunt and luminescence coupling. The methods are demonstrated for the first time to effectively eliminate the measurement artifacts.
ContributorsLi, Jingjing (Author) / Zhang, Yong-Hang (Thesis advisor) / Tao, Meng (Committee member) / Schroder, Dieter (Committee member) / Vasileska, Dragica (Committee member) / Arizona State University (Publisher)
Created2012
Description
Advances in semiconductor technology have brought computer-based systems intovirtually all aspects of human life. This unprecedented integration of semiconductor based systems in our lives has significantly increased the domain and the number
of safety-critical applications – application with unacceptable consequences of failure. Software-level error resilience schemes are attractive because they can provide commercial-off-the-shelf microprocessors with adaptive and scalable reliability.
Among all software-level error resilience solutions, in-application instruction replication based approaches have been widely used and are deemed to be the most effective. However, existing instruction-based replication schemes only protect some part of computations i.e. arithmetic and logical instructions and leave the rest as unprotected. To improve the efficacy of instruction-level redundancy-based approaches, we developed several error detection and error correction schemes. nZDC (near Zero silent
Data Corruption) is an instruction duplication scheme which protects the execution of whole application. Rather than detecting errors on register operands of memory and control flow operations, nZDC checks the results of such operations. nZDC en
sures the correct execution of memory write instruction by reloading stored value and checking it against redundantly computed value. nZDC also introduces a novel control flow checking mechanism which replicates compare and branch instructions and
detects both wrong direction branches as well as unwanted jumps. Fault injection experiments show that nZDC can improve the error coverage of the state-of-the-art schemes by more than 10x, without incurring any more performance penalty. Further
more, we introduced two error recovery solutions. InCheck is our backward recovery solution which makes light-weighted error-free checkpoints at the basic block granularity. In the case of error, InCheck reverts the program execution to the beginning of last executed basic block and resumes the execution by the aid of preserved in formation. NEMESIS is our forward recovery scheme which runs three versions of computation and detects errors by checking the results of all memory write and branch
operations. In the case of a mismatch, NEMESIS diagnosis routine decides if the error is recoverable. If yes, NEMESIS recovery routine reverts the effect of error from the program state and resumes program normal execution from the error detection
point.
of safety-critical applications – application with unacceptable consequences of failure. Software-level error resilience schemes are attractive because they can provide commercial-off-the-shelf microprocessors with adaptive and scalable reliability.
Among all software-level error resilience solutions, in-application instruction replication based approaches have been widely used and are deemed to be the most effective. However, existing instruction-based replication schemes only protect some part of computations i.e. arithmetic and logical instructions and leave the rest as unprotected. To improve the efficacy of instruction-level redundancy-based approaches, we developed several error detection and error correction schemes. nZDC (near Zero silent
Data Corruption) is an instruction duplication scheme which protects the execution of whole application. Rather than detecting errors on register operands of memory and control flow operations, nZDC checks the results of such operations. nZDC en
sures the correct execution of memory write instruction by reloading stored value and checking it against redundantly computed value. nZDC also introduces a novel control flow checking mechanism which replicates compare and branch instructions and
detects both wrong direction branches as well as unwanted jumps. Fault injection experiments show that nZDC can improve the error coverage of the state-of-the-art schemes by more than 10x, without incurring any more performance penalty. Further
more, we introduced two error recovery solutions. InCheck is our backward recovery solution which makes light-weighted error-free checkpoints at the basic block granularity. In the case of error, InCheck reverts the program execution to the beginning of last executed basic block and resumes the execution by the aid of preserved in formation. NEMESIS is our forward recovery scheme which runs three versions of computation and detects errors by checking the results of all memory write and branch
operations. In the case of a mismatch, NEMESIS diagnosis routine decides if the error is recoverable. If yes, NEMESIS recovery routine reverts the effect of error from the program state and resumes program normal execution from the error detection
point.
ContributorsDidehban, Moslem (Author) / Shrivastava, Aviral (Thesis advisor) / Wu, Carole-Jean (Committee member) / Clark, Lawrence (Committee member) / Mahlke, Scott (Committee member) / Arizona State University (Publisher)
Created2018
Description
Potential-Induced Degradation (PID) is an extremely serious photovoltaic (PV) durability issue significantly observed in crystalline silicon PV modules due to its rapid power degradation, particularly when compared to other PV degradation modes. The focus of this dissertation is to understand PID mechanisms and to develop PID-free cells and modules. PID-affected modules have been claimed to be fully recovered by high temperature and reverse potential treatments. However, the results obtained in this work indicate that the near-full recovery of efficiency can be achieved only at high irradiance conditions, but the full recovery of efficiency at low irradiance levels, of shunt resistance, and of quantum efficiency (QE) at short wavelengths could not be achieved. The QE loss observed at short wavelengths was modeled by changing the front surface recombination velocity. The QE scaling error due to a measurement on a PID shunted cell was addressed by developing a very low input impedance accessory applicable to an existing QE system. The impacts of silicon nitride (SiNx) anti-reflection coating (ARC) refractive index (RI) and emitter sheet resistance on PID are presented. Low RI ARC cells (1.87) were observed to be PID-susceptible whereas high RI ARC cells (2.05) were determined to be PID-resistant using a method employing high dose corona charging followed by time-resolved measurement of surface voltage. It has been demonstrated that the PID could be prevented by deploying an emitter having a low sheet resistance (~ 60 /sq) even if a PID-susceptible ARC is used in a cell. Secondary ion mass spectroscopy (SIMS) results suggest that a high phosphorous emitter layer hinders sodium transport, which is responsible for the PID. Cells can be screened for PID susceptibility by illuminated lock-in thermography (ILIT) during the cell fabrication process, and the sample structure for this can advantageously be simplified as long as the sample has the SiNx ARC and an aluminum back surface field. Finally, this dissertation presents a prospective method for eliminating or minimizing the PID issue either in the factory during manufacturing or in the field after system installation. The method uses commercially available, thin, and flexible Corning® Willow® Glass sheets or strips on the PV module glass superstrates, disrupting the current leakage path from the cells to the grounded frame.
ContributorsOh, Jaewon (Author) / Bowden, Stuart (Thesis advisor) / Tamizhmani, Govindasamy (Thesis advisor) / Honsberg, Christiana (Committee member) / Hacke, Peter (Committee member) / Schroder, Dieter (Committee member) / Arizona State University (Publisher)
Created2016
Description
Neural networks are increasingly becoming attractive solutions for automated systems within automotive, aerospace, and military industries.Since many applications in such fields are both real-time and safety-critical, strict performance and reliability constraints must be considered. To achieve high performance, specialized architectures are required.Given that over 90% of the workload in modern neural network topologies is dominated by matrix multiplication, accelerating said algorithm becomes of paramount importance.
Modern neural network accelerators, such as Xilinx's Deep Processing Unit (DPU), adopt efficient systolic-like architectures. Thanks to their high degree of parallelism and design flexibility, Field-Programmable Gate Arrays (FPGAs) are among the most promising devices for speeding up matrix multiplication and neural network computation.However, SRAM-based FPGAs are also known to suffer from radiation-induced upsets in their configuration memories. To achieve high reliability, hardening strategies must be put in place.However, traditional modular redundancy of inherently expensive modules is not always feasible due to limited resource availability on target devices.
Therefore, more efficient and cleverly designed hardening methods become a necessity.
For instance, Algorithm-Based Fault-Tolerance (ABFT) exploits algorithm characteristics to deliver error detection/correction capabilities at significantly lower costs. First, experimental results with Xilinx's DPU indicate that failure rates can be over twice as high as the limits specified for terrestrial applications.In other words, the undeniable need for hardening in the state-of-the-art neural network accelerator for FPGAs is demonstrated. Later, an extensive multi-level fault propagation analysis is presented, and an ultra-low-cost algorithm-based error detection strategy for matrix multiplication is proposed.By considering the specifics of FPGAs' fault model, this novel hardening method decreases costs of implementation by over a polynomial degree, when compared to state-of-the-art solutions.
A corresponding architectural implementation is suggested, incurring area and energy overheads lower than 1% for the vast majority of systolic arrays dimensions. Finally, the impact of fundamental design decisions, such as data precision in processing elements, and overall degree of parallelism, on the reliability of hypothetical neural network accelerators is experimentally investigated.A novel way of predicting the compound failure rate of inherently inaccurate algorithms/applications in the presence of radiation is also provided.
ContributorsLibano, Fabiano (Author) / Brunhaver, John (Thesis advisor) / Clark, Lawrence (Committee member) / Quinn, Heather (Committee member) / Rech, Paolo (Committee member) / Arizona State University (Publisher)
Created2021