Variation aware analysis of bridging fault testing

This paper investigates the impact of process variation on test quality with regard to resistive bridging faults. The input logic threshold voltage and gate drive strength parameters are analyzed regarding their process variation induced influence on test quality. The impact of process variation on test quality is studied in terms of test escapes and measured by a robustness metric. It is shown that some bridges are sensitive to process variation in terms of logic behavior, but such variation does not necessarily compromise test quality if the test has high robustness. Experimental results of Monte-Carlo simulation based on recent process variation statistics are presented for ISCAS85 and -89 benchmark circuits, using a 45nm gate library and realistic bridges. The results show that tests generated without consideration of process variation are inadequate in terms of test quality, particularly for small test sets. On the other hand, larger test sets detect more of the logic faults introduced by process variation and have higher test quality

Towards Structural Testing of Superconductor Electronics

Many of the semiconductor technologies are already\ud facing limitations while new-generation data and\ud telecommunication systems are implemented. Although in\ud its infancy, superconductor electronics (SCE) is capable of\ud handling some of these high-end tasks. We have started a\ud defect-oriented test methodology for SCE, so that reliable\ud systems can be implemented in this technology. In this\ud paper, the details of the study on the Rapid Single-Flux\ud Quantum (RSFQ) process are presented. We present\ud common defects in the SCE processes and corresponding\ud test methodologies to detect them. The (measurement)\ud results prove that we are able to detect possible random\ud defects for statistical purposes in yield analysis. This\ud paper also presents possible test methodologies for RSFQ\ud circuits based on defect oriented testing (DOT)

Investigation into voltage and process variation-aware manufacturing test

Increasing integration and complexity in IC design provides challenges for manufacturing testing. This thesis studies how process and supply voltage variation influence defect behaviour to determine the impact on manufacturing test cost and quality. The focus is on logic testing of static CMOS designs with respect to two important defect types in deep submicron CMOS: resistive bridges and full opens. The first part of the thesis addresses testing for resistive bridge defects in designs with multiple supply voltage settings. To enable analysis, a fault simulator is developed using a supply voltage-aware model for bridge defect behaviour. The analysis shows that for high defect coverage it is necessary to perform test for more than one supply voltage setting, due to supply voltage-dependent behaviour. A low-cost and effective test method is presented consisting of multi-voltage test generation that achieves high defect coverage and test set size reduction without compromise to defect coverage. Experiments on synthesised benchmarks with realistic bridge locations validate the proposed method.The second part focuses on the behaviour of full open defects under supply voltage variation. The aim is to determine the appropriate value of supply voltage to use when testing. Two models are considered for the behaviour of full open defects with and without gate tunnelling leakage influence. Analysis of the supply voltage-dependent behaviour of full open defects is performed to determine if it is required to test using more than one supply voltage to detect all full open defects. Experiments on synthesised benchmarks using an extended version of the fault simulator tool mentioned above, measure the quantitative impact of supply voltage variation on defect coverage.The final part studies the impact of process variation on the behaviour of bridge defects. Detailed analysis using synthesised ISCAS benchmarks and realistic bridge model shows that process variation leads to additional faults. If process variation is not considered in test generation, the test will fail to detect some of these faults, which leads to test escapes. A novel metric to quantify the impact of process variation on test quality is employed in the development of a new test generation tool, which achieves high bridge defect coverage. The method achieves a user-specified test quality with test sets which are smaller than test sets generated without consideration of process variation

Fault modelling and accelerated simulation of integrated circuits manufacturing defects under process variation

As silicon manufacturing process scales to and beyond the 65-nm node, process variation can no longer be ignored. The impact of process variation on integrated circuit performance and power has received significant research input. Variation-aware test, on the other hand, is a relatively new research area that is currently receiving attention worldwide.Research has shown that test without considering process variation may lead to loss of test quality. Fault modelling and simulation serve as a backbone of manufacturing test. This thesis is concerned with developing efficient fault modelling techniques and simulation methodologies that take into account the effect of process variation on manufacturing defects with particular emphasis on resistive bridges and resistive opens.The first contribution of this thesis addresses the problem of long computation time required to generate logic fault of resistive bridges under process variation by developing a fast and accurate modelling technique to model logic fault behaviour of resistive bridges.The new technique is implemented by employing two efficient voltage calculation algorithms to calculate the logic threshold voltage of driven gates and critical resistance of a fault-site to enable the computation of bridge logic faults without using SPICE. Simulation results show that the technique is fast (on average 53 times faster) and accurate (worst case is 2.64% error) when compared with HSPICE. The second contribution analyses the complexity of delay fault simulation of resistive bridges to reduce the computation time of delay fault when considering process variation. An accelerated delay fault simulation methodology of resistive bridges is developed by employing a three-step strategy to speed up the calculation of transient gate output voltage which is needed to accurately compute delay faults. Simulation results show that the methodology is on average 17.4 times faster, with 5.2% error in accuracy, when compared with HSPICE. The final contribution presents an accelerated simulation methodology of resistive opens to address the problem of long simulation time of delay fault when considering process variation. The methodology is implemented by using two efficient algorithms to accelerate the computation of transient gate output voltage and timing critical resistance of an open fault-site. Simulation results show that the methodology is on average up to 52 times faster than HSPICE, with 4.2% error in accuracy

Leakage Current Analysis for Diagnosis of Bridge Defects in Power-Gating Designs

Manufacturing defects that do not affect the functional operation of low power Integrated Circuits (ICs) can nevertheless impact their power saving capability. We show that stuck-ON faults on the power switches and resistive bridges between the power networks can impair the power saving capability of power-gating designs. For quantifying the impact of such faults on the power savings of power-gating designs, we propose a diagnosis technique that targets bridges between the power networks. The proposed technique is based on the static power analysis of a power-gating design in stand-by mode and it utilizes a novel on-chip signature generation unit, which is sensitive to the voltage level between power rails, the measurements of which are processed off-line for the diagnosis of bridges that can adversely affect power savings. We explore, through SPICE simulation of the largest IWLS’05 benchmarks synthesised using a 32 nm CMOS technology, the trade-offs achieved by the proposed technique between diagnosis accuracy and area cost and we evaluate its robustness against process variation. The proposed technique achieves a diagnosis resolution that is higher than 98.6% and 97.9% for bridges of R ≳ 10MΩ(weak bridges) and bridges of R ≲ 10MΩ (strong bridges), respectively, and a diagnosis accuracy higher than 94.5% for all the examined defects. The area overhead is small and scalable: it is found to be 1.8% and 0.3% for designs with 27K and 157K gate equivalents, respectively

Comparing the impact of power supply voltage on CMOS-and FinFET-based SRAMs in the presence of resistive defects

CMOS technology scaling has reached its limit at the 22 nm technology node due to several factors including Process Variations (PV), increased leakage current, Random Dopant Fluctuation (RDF), and mainly the Short-Channel Effect (SCE). In order to continue the miniaturization process via technology down-scaling while preserving system reliability and performance, Fin Field-Effect Transistors (FinFETs) arise as an alternative to CMOS transistors. In parallel, Static Random-Access Memories (SRAMs) increasingly occupy great part of Systems-on-Chips’ (SoCs) silicon area, making their reliability an important issue. SRAMs are designed to reach densities at the limit of the manufacturing process, making this component susceptible to manufacturing defects, including the resistive ones. Such defects may cause dynamic faults during the circuits’ lifetime, an important cause of test escape. Thus, the identification of the proper faulty behavior taking different operating conditions into account is considered crucial to guarantee the development of more suitable test methodologies. In this context, a comparison between the behavior of a 22 nm CMOS-based and a 20 nm FinFET-based SRAM in the presence of resistive defects is carried out considering different power supply voltages. In more detail, the behavior of defective cells operating under different power supply voltages has been investigated performing SPICE simulations. Results show that the power supply voltage plays an important role in the faulty behavior of both CMOS- and FinFET-based SRAM cells in the presence of resistive defects but demonstrate to be more expressive when considering the FinFET-based memories. Studying different operating temperatures, the results show an expressively higher occurrence of dynamic faults in FinFET-based SRAMs when compared to CMOS technology

Fault simulation for structural testing of analogue integrated circuits

In this thesis the ANTICS analogue fault simulation software is described which provides a statistical approach to fault simulation for accurate analogue IC test evaluation. The traditional figure of fault coverage is replaced by the average probability of fault detection. This is later refined by considering the probability of fault occurrence to generate a more realistic, weighted test metric. Two techniques to reduce the fault simulation time are described, both of which show large reductions in simulation time with little loss of accuracy. The final section of the thesis presents an accurate comparison of three test techniques and an evaluation of dynamic supply current monitoring. An increase in fault detection for dynamic supply current monitoring is obtained by removing the DC component of the supply current prior to measurement

Test Quality Analysis and Improvement for an Embedded Asynchronous FIFO

Embedded First-InFirst-Out (FIFO) memories are increasingly used in many IC designs.We have created a new full-custom embedded FIFO module withasynchronous read and write clocks, which is at least a factor twosmaller and also faster than SRAM-based and standard-cell-basedcounterparts. The detection qualities of the FIFO test for bothhard and weak resistive shorts and opens have been analyzed by anIFA-like method based on analog simulation. The defect coverage ofthe initial FIFO test for shorts in the bit-cell matrix has beenimproved by inclusion of an additional data background andlow-voltage testing; for low-resistant shorts, 100% defect coverageis obtained. The defect coverage for opens has been improved by anew test procedure which includes waitingperiods

Technology and layout-related testing of static random-access memories

Static random-access memories (SRAMs) exhibit faults that are electrical in nature. Functional and electrical testing are performed to diagnose faulty operation. These tests are usually designed from simple fault models that describe the chip interface behavior without a thorough analysis of the chip layout and technology. However, there are certain technology and layout-related defects that are internal to the chip and are mostly time-dependent in nature. The resulting failures may or may not seriously degrade the input/output interface behavior. They may show up as electrical faults (such as a slow access fault) and/or functional faults (such as a pattern sensitive fault). However, these faults cannot be described properly with the functional fault models because these models do not take timing into account. Also, electrical fault models that describe merely the input/output interface behavior are inadequate to characterize every possible defect in the basic SRAM cell. Examples of faults produced by these defects are: (a) static data loss, (b) abnormally high currents drawn from the power supply, etc. Generating tests for such faults often requires a thorough understanding and analysis of the circuit technology and layout. In this article, we shall examine ways to characterize and test such faults. We shall divide such faults into two categories depending on the types of SRAMs they effect—silicon SRAMs and GaAs SRAMs.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/43015/1/10836_2004_Article_BF00972519.pd