105 research outputs found
Quiescent current testing of CMOS data converters
Power supply quiescent current (IDDQ) testing has been very effective in VLSI circuits designed in CMOS processes detecting physical defects such as open and shorts and bridging defects. However, in sub-micron VLSI circuits, IDDQ is masked by the increased subthreshold (leakage) current of MOSFETs affecting the efficiency of I¬DDQ testing. In this work, an attempt has been made to perform robust IDDQ testing in presence of increased leakage current by suitably modifying some of the test methods normally used in industry. Digital CMOS integrated circuits have been tested successfully using IDDQ and IDDQ methods for physical defects. However, testing of analog circuits is still a problem due to variation in design from one specific application to other. The increased leakage current further complicates not only the design but also testing. Mixed-signal integrated circuits such as the data converters are even more difficult to test because both analog and digital functions are built on the same substrate. We have re-examined both IDDQ and IDDQ methods of testing digital CMOS VLSI circuits and added features to minimize the influence of leakage current. We have designed built-in current sensors (BICS) for on-chip testing of analog and mixed-signal integrated circuits. We have also combined quiescent current testing with oscillation and transient current test techniques to map large number of manufacturing defects on a chip. In testing, we have used a simple method of injecting faults simulating manufacturing defects invented in our VLSI research group. We present design and testing of analog and mixed-signal integrated circuits with on-chip BICS such as an operational amplifier, 12-bit charge scaling architecture based digital-to-analog converter (DAC), 12-bit recycling architecture based analog-to-digital converter (ADC) and operational amplifier with floating gate inputs. The designed circuits are fabricated in 0.5 μm and 1.5 μm n-well CMOS processes and tested. Experimentally observed results of the fabricated devices are compared with simulations from SPICE using MOS level 3 and BSIM3.1 model parameters for 1.5 μm and 0.5 μm n-well CMOS technologies, respectively. We have also explored the possibility of using noise in VLSI circuits for testing defects and present the method we have developed
Integrated circuit outlier identification by multiple parameter correlation
Semiconductor manufacturers must ensure that chips conform to their specifications before they are shipped to customers. This is achieved by testing various parameters of a chip to determine whether it is defective or not. Separating defective chips from fault-free ones is relatively straightforward for functional or other Boolean tests that produce a go/no-go type of result. However, making this distinction is extremely challenging for parametric tests. Owing to continuous distributions of parameters, any pass/fail threshold results in yield loss and/or test escapes. The continuous advances in process technology, increased process variations and inaccurate fault models all make this even worse. The pass/fail thresholds for such tests are usually set using prior experience or by a combination of visual inspection and engineering judgment. Many chips have parameters that exceed certain thresholds but pass Boolean tests. Owing to the imperfect nature of tests, to determine whether these chips (called "outliers") are indeed defective is nontrivial. To avoid wasted investment in packaging or further testing it is important to screen defective chips early in a test flow. Moreover, if seemingly strange behavior of outlier chips can be explained with the help of certain process parameters or by correlating additional test data, such chips can be retained in the test flow before they are proved to be fatally flawed. In this research, we investigate several methods to identify true outliers (defective chips, or chips that lead to functional failure) from apparent outliers (seemingly defective, but fault-free chips). The outlier identification methods in this research primarily rely on wafer-level spatial correlation, but also use additional test parameters. These methods are evaluated and validated using industrial test data. The potential of these methods to reduce burn-in is discussed
Voltage sensing based built-in current sensor for IDDQ test
Quiescent current leakage test of the VDD supply (IDDQ Test) has been proven an
effective way to screen out defective chips in manufacturing of Integrated Circuits (IC).
As technology advances, the traditional IDDQ test is facing more and more challenges. In
this research, a practical built-in current sensor (BICS) is proposed and the design is
verified by three generations of test chips. The BICS detects the signal by sensing the
voltage drop on supply lines of the circuit under test (CUT). Then the sensor performs
analog-to-digital conversion of the input signal using a stochastic process with scan chain
readout. Self-calibration and digital chopping are used to minimize offset and low
frequency noise and drift. This non-invasive procedure avoids any performance
degradation of the CUT. The measurement results of test chips are presented. The sensor
achieves a high IDDQ resolution with small chip area overhead. This will enable IDDQ of
future technology generations
AI/ML Algorithms and Applications in VLSI Design and Technology
An evident challenge ahead for the integrated circuit (IC) industry in the
nanometer regime is the investigation and development of methods that can
reduce the design complexity ensuing from growing process variations and
curtail the turnaround time of chip manufacturing. Conventional methodologies
employed for such tasks are largely manual; thus, time-consuming and
resource-intensive. In contrast, the unique learning strategies of artificial
intelligence (AI) provide numerous exciting automated approaches for handling
complex and data-intensive tasks in very-large-scale integration (VLSI) design
and testing. Employing AI and machine learning (ML) algorithms in VLSI design
and manufacturing reduces the time and effort for understanding and processing
the data within and across different abstraction levels via automated learning
algorithms. It, in turn, improves the IC yield and reduces the manufacturing
turnaround time. This paper thoroughly reviews the AI/ML automated approaches
introduced in the past towards VLSI design and manufacturing. Moreover, we
discuss the scope of AI/ML applications in the future at various abstraction
levels to revolutionize the field of VLSI design, aiming for high-speed, highly
intelligent, and efficient implementations
Design and debugging of multi-step analog to digital converters
With the fast advancement of CMOS fabrication technology, more and more signal-processing functions are implemented in the digital domain for a lower cost, lower power consumption, higher yield, and higher re-configurability. The trend of increasing integration level for integrated circuits has forced the A/D converter interface to reside on the same silicon in complex mixed-signal ICs containing mostly digital blocks for DSP and control. However, specifications of the converters in various applications emphasize high dynamic range and low spurious spectral performance. It is nontrivial to achieve this level of linearity in a monolithic environment where post-fabrication component trimming or calibration is cumbersome to implement for certain applications or/and for cost and manufacturability reasons. Additionally, as CMOS integrated circuits are accomplishing unprecedented integration levels, potential problems associated with device scaling – the short-channel effects – are also looming large as technology strides into the deep-submicron regime. The A/D conversion process involves sampling the applied analog input signal and quantizing it to its digital representation by comparing it to reference voltages before further signal processing in subsequent digital systems. Depending on how these functions are combined, different A/D converter architectures can be implemented with different requirements on each function. Practical realizations show the trend that to a first order, converter power is directly proportional to sampling rate. However, power dissipation required becomes nonlinear as the speed capabilities of a process technology are pushed to the limit. Pipeline and two-step/multi-step converters tend to be the most efficient at achieving a given resolution and sampling rate specification. This thesis is in a sense unique work as it covers the whole spectrum of design, test, debugging and calibration of multi-step A/D converters; it incorporates development of circuit techniques and algorithms to enhance the resolution and attainable sample rate of an A/D converter and to enhance testing and debugging potential to detect errors dynamically, to isolate and confine faults, and to recover and compensate for the errors continuously. The power proficiency for high resolution of multi-step converter by combining parallelism and calibration and exploiting low-voltage circuit techniques is demonstrated with a 1.8 V, 12-bit, 80 MS/s, 100 mW analog to-digital converter fabricated in five-metal layers 0.18-µm CMOS process. Lower power supply voltages significantly reduce noise margins and increase variations in process, device and design parameters. Consequently, it is steadily more difficult to control the fabrication process precisely enough to maintain uniformity. Microscopic particles present in the manufacturing environment and slight variations in the parameters of manufacturing steps can all lead to the geometrical and electrical properties of an IC to deviate from those generated at the end of the design process. Those defects can cause various types of malfunctioning, depending on the IC topology and the nature of the defect. To relive the burden placed on IC design and manufacturing originated with ever-increasing costs associated with testing and debugging of complex mixed-signal electronic systems, several circuit techniques and algorithms are developed and incorporated in proposed ATPG, DfT and BIST methodologies. Process variation cannot be solved by improving manufacturing tolerances; variability must be reduced by new device technology or managed by design in order for scaling to continue. Similarly, within-die performance variation also imposes new challenges for test methods. With the use of dedicated sensors, which exploit knowledge of the circuit structure and the specific defect mechanisms, the method described in this thesis facilitates early and fast identification of excessive process parameter variation effects. The expectation-maximization algorithm makes the estimation problem more tractable and also yields good estimates of the parameters for small sample sizes. To allow the test guidance with the information obtained through monitoring process variations implemented adjusted support vector machine classifier simultaneously minimize the empirical classification error and maximize the geometric margin. On a positive note, the use of digital enhancing calibration techniques reduces the need for expensive technologies with special fabrication steps. Indeed, the extra cost of digital processing is normally affordable as the use of submicron mixed signal technologies allows for efficient usage of silicon area even for relatively complex algorithms. Employed adaptive filtering algorithm for error estimation offers the small number of operations per iteration and does not require correlation function calculation nor matrix inversions. The presented foreground calibration algorithm does not need any dedicated test signal and does not require a part of the conversion time. It works continuously and with every signal applied to the A/D converter. The feasibility of the method for on-line and off-line debugging and calibration has been verified by experimental measurements from the silicon prototype fabricated in standard single poly, six metal 0.09-µm CMOS process
Design-for-delay-testability techniques for high-speed digital circuits
The importance of delay faults is enhanced by the ever increasing clock rates and decreasing geometry sizes of nowadays' circuits. This thesis focuses on the development of Design-for-Delay-Testability (DfDT) techniques for high-speed circuits and embedded cores. The rising costs of IC testing and in particular the costs of Automatic Test Equipment are major concerns for the semiconductor industry. To reverse the trend of rising testing costs, DfDT is\ud
getting more and more important
Algorithms for Power Aware Testing of Nanometer Digital ICs
At-speed testing of deep-submicron digital very large scale integrated (VLSI) circuits
has become mandatory to catch small delay defects. Now, due to continuous shrinking
of complementary metal oxide semiconductor (CMOS) transistor feature size, power
density grows geometrically with technology scaling. Additionally, power dissipation
inside a digital circuit during the testing phase (for test vectors under all fault models
(Potluri, 2015)) is several times higher than its power dissipation during the normal
functional phase of operation. Due to this, the currents that flow in the power grid during
the testing phase, are much higher than what the power grid is designed for (the
functional phase of operation). As a result, during at-speed testing, the supply grid
experiences unacceptable supply IR-drop, ultimately leading to delay failures during
at-speed testing. Since these failures are specific to testing and do not occur during
functional phase of operation of the chip, these failures are usually referred to false
failures, and they reduce the yield of the chip, which is undesirable.
In nanometer regime, process parameter variations has become a major problem.
Due to the variation in signalling delays caused by these variations, it is important to
perform at-speed testing even for stuck faults, to reduce the test escapes (McCluskey
and Tseng, 2000; Vorisek et al., 2004). In this context, the problem of excessive peak
power dissipation causing false failures, that was addressed previously in the context of
at-speed transition fault testing (Saxena et al., 2003; Devanathan et al., 2007a,b,c), also
becomes prominent in the context of at-speed testing of stuck faults (Maxwell et al.,
1996; McCluskey and Tseng, 2000; Vorisek et al., 2004; Prabhu and Abraham, 2012;
Potluri, 2015; Potluri et al., 2015). It is well known that excessive supply IR-drop during
at-speed testing can be kept under control by minimizing switching activity during
testing (Saxena et al., 2003). There is a rich collection of techniques proposed in the past
for reduction of peak switching activity during at-speed testing of transition/delay faults
ii
in both combinational and sequential circuits. As far as at-speed testing of stuck faults
are concerned, while there were some techniques proposed in the past for combinational
circuits (Girard et al., 1998; Dabholkar et al., 1998), there are no techniques concerning
the same for sequential circuits. This thesis addresses this open problem. We
propose algorithms for minimization of peak switching activity during at-speed testing
of stuck faults in sequential digital circuits under the combinational state preservation
scan (CSP-scan) architecture (Potluri, 2015; Potluri et al., 2015). First, we show that,
under this CSP-scan architecture, when the test set is completely specified, the peak
switching activity during testing can be minimized by solving the Bottleneck Traveling
Salesman Problem (BTSP). This mapping of peak test switching activity minimization
problem to BTSP is novel, and proposed for the first time in the literature.
Usually, as circuit size increases, the percentage of don’t cares in the test set increases.
As a result, test vector ordering for any arbitrary filling of don’t care bits
is insufficient for producing effective reduction in switching activity during testing of
large circuits. Since don’t cares dominate the test sets for larger circuits, don’t care
filling plays a crucial role in reducing switching activity during testing. Taking this
into consideration, we propose an algorithm, XStat, which is capable of performing test
vector ordering while preserving don’t care bits in the test vectors, following which, the
don’t cares are filled in an intelligent fashion for minimizing input switching activity,
which effectively minimizes switching activity inside the circuit (Girard et al., 1998).
Through empirical validation on benchmark circuits, we show that XStat minimizes
peak switching activity significantly, during testing.
Although XStat is a very powerful heuristic for minimizing peak input-switchingactivity,
it will not guarantee optimality. To address this issue, we propose an algorithm
that uses Dynamic Programming to calculate the lower bound for a given sequence
of test vectors, and subsequently uses a greedy strategy for filling don’t cares in this
sequence to achieve this lower bound, thereby guaranteeing optimality. This algorithm,
which we refer to as DP-fill in this thesis, provides the globally optimal solution for
minimizing peak input-switching-activity and also is the best known in the literature
for minimizing peak input-switching-activity during testing. The proof of optimality of
DP-fill in minimizing peak input-switching-activity is also provided in this thesis
FEASIBILITY INVESTIGATION OF FAULT DIAGNOSIS USING ELECTROMAGNETIC ANALYSIS OF PLANAR STRUCTURES
Nowadays, circuit design technologies have progressively advanced to cope
with the high performance of the electronic components. With the circuit design
advancement,the technology for IC fabrication has moved to deep submicron era. As
the circuit sizes continue to scale down to nanoscale, the number of transistors and
interconnects on the circuits tends to grow as well. This challengesthe circuit testing
by introducing high number of possible faults on the circuit. Consequently, the
product qualitycontrol has become more challenging. The product quality could drop
significantly ifthe circuits are not designed to be testable
Effective network grid synthesis and optimization for high performance very large scale integration system design
制度:新 ; 文部省報告番号:甲2642号 ; 学位の種類:博士(工学) ; 授与年月日:2008/3/15 ; 早大学位記番号:新480
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