Dynamic Voltage Scaling Aware Delay Fault Testing

The application of Dynamic Voltage Scaling (DVS) to reduce energy consumption may have a detrimental impact on the quality of manufacturing tests employed to detect permanent faults. This paper analyses the influence of different voltage/frequency settings on fault detection within a DVS application. In particular, the effect of supply voltage on different types of delay faults is considered. This paper presents a study of these problems with simulation results. We have demonstrated that the test application time increases as we reduce the test voltage. We have also shown that for newer technologies we do not have to go to very low voltage levels for delay fault testing. We conclude that it is necessary to test at more than one operating voltage and that the lowest operating voltage does not necessarily give the best fault cover

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

Statistical static timing analysis considering process variations and crosstalk

Increasing relative semiconductor process variations are making the prediction of realistic worst-case integrated circuit delay or sign-off yield more difficult. As process geometries shrink, intra-die variations have become dominant and it is imperative to model them to obtain accurate timing analysis results. In addition, intra-die process variations are spatially correlated due to pattern dependencies in the manufacturing process. Any statistical static timing analysis (SSTA) tool is incomplete without a model for signal crosstalk, as critical path delays can increase or decrease depending on the switching of capacitively coupled nets. The coupled signal timing in turn depends on the process variations. This work describes an SSTA tool that models signal crosstalk and spatial correlation in intra-die process variations, along with gradients and inter-die variations

Longest path selection for delay test under process variation

Abstract—Under manufacturing process variation, a path through a net is called longest if there exists a process condition under which the path has the maximum delay among all paths through the net. There are often multiple longest paths for each net, due to different process conditions. In addition, a local defect, such as resistive open or a resistive bridge, increases the delay of the affected net. To detect delay faults due to local defects and process variation, it is necessary to test all longest paths through each net. Previous approaches to this problem were inefficient because of the large number of paths that are not longest. This paper presents an efficient method to generate the set of longest paths for delay test under process variation. To capture both structural and process correlation between path delays, we use linear delay functions to express path delays under process variation. A novel technique is proposed to prune paths that are not longest, resulting in a significant reduction in the number of paths. In experiments on ISCAS circuits, our number of longest paths is 1 % to 6 % of the previous best approach, with 300X less running time

Fault modeling, delay evaluation and path selection for delay test under process variation in nano-scale VLSI circuits

Delay test in nano-scale VLSI circuits becomes more difficult with shrinking technology feature sizes and rising clock frequencies. In this dissertation, we study three challenging issues in delay test: fault modeling, variational delay evaluation and path selection under process variation. Previous research of fault modeling on resistive spot defects, such as resistive opens and bridges in the interconnect, and resistive shorts in devices, lacked an accurate fault model. As a result it was difficult to perform fault simulation and select the best vectors. Conventional methods to compute variational delay under process variation are either slow or inaccurate. On the problem of path selection under process variation, previous approaches either choose too many paths, or missed the path that is necessary to be tested. We present new solutions in this dissertation. A new fault model that clearly and comprehensively expresses the relationship between electrical behaviors and resistive spots is proposed. Then the effect of process variations on path delays is modeled with a linear function and a fast method to compute coefficients of the linear function is also derived. Finally, we present the new path pruning algorithms that efficiently prune unimportant paths for test, and as a result we select as few as possible paths for test while the fault coverage is satisfied. The experimental results show that the new solutions are efficient and accurate

High Quality Compact Delay Test Generation

Delay testing is used to detect timing defects and ensure that a circuit meets its timing specifications. The growing need for delay testing is a result of the advances in deep submicron (DSM) semiconductor technology and the increase in clock frequency. Small delay defects that previously were benign now produce delay faults, due to reduced timing margins. This research focuses on the development of new test methods for small delay defects, within the limits of affordable test generation cost and pattern count. First, a new dynamic compaction algorithm has been proposed to generate compacted test sets for K longest paths per gate (KLPG) in combinational circuits or scan-based sequential circuits. This algorithm uses a greedy approach to compact paths with non-conflicting necessary assignments together during test generation. Second, to make this dynamic compaction approach practical for industrial use, a recursive learning algorithm has been implemented to identify more necessary assignments for each path, so that the path-to-test-pattern matching using necessary assignments is more accurate. Third, a realistic low cost fault coverage metric targeting both global and local delay faults has been developed. The metric suggests the test strategy of generating a different number of longest paths for each line in the circuit while maintaining high fault coverage. The number of paths and type of test depends on the timing slack of the paths under this metric. Experimental results for ISCAS89 benchmark circuits and three industry circuits show that the pattern count of KLPG can be significantly reduced using the proposed methods. The pattern count is comparable to that of transition fault test, while achieving higher test quality. Finally, the proposed ATPG methodology has been applied to an industrial quad-core microprocessor. FMAX testing has been done on many devices and silicon data has shown the benefit of KLPG test

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

Fault simulation and test generation for small delay faults

Delay faults are an increasingly important test challenge. Traditional delay fault models are incomplete in that they model only a subset of delay defect behaviors. To solve this problem, a more realistic delay fault model has been developed which models delay faults caused by the combination of spot defects and parametric process variation. According to the new model, a realistic delay fault coverage metric has been developed. Traditional path delay fault coverage metrics result in unrealistically low fault coverage, and the real test quality is not reflected. The new metric uses a statistical approach and the simulation based fault coverage is consistent with silicon data. Fast simulation algorithms are also included in this dissertation. The new metric suggests that testing the K longest paths per gate (KLPG) has high detection probability for small delay faults under process variation. In this dissertation, a novel automatic test pattern generation (ATPG) methodology to find the K longest testable paths through each gate for both combinational and sequential circuits is presented. Many techniques are used to reduce search space and CPU time significantly. Experimental results show that this methodology is efficient and able to handle circuits with an exponential number of paths, such as ISCAS85 benchmark circuit c6288. The ATPG methodology has been implemented on industrial designs. Speed binning has been done on many devices and silicon data has shown significant benefit of the KLPG test, compared to several traditional delay test approaches