9360339
An evaluation of pseudo random testing for detecting real defects
Research has shown that single stuck-at fault (SSF) N-detect test sets are effective for detecting defects not modeled by the SSF model. Experimental results showed N-detect coverage is a good metric for determining test quality. In this paper, we examine the test quality of pseudo-random Built-in-Self-Test (BIST) patterns by quantifying the relations between their N-detect coverage and test length. We theoretically derive bounds on the minimum test length of pseudo-random patterns required to achieve a given N-detect coverage. For faults with high detectability, the expected test length for N-detection is around N times the expected test length for single detection. However, for faults with low detectability, the expected test length for N-detection can be NlogN times the expected test length for detecting the fault only once; this increases the test length significantly. We also introduce the idea of effective detectability which is important for analyzing the effectiveness of BIST techniques for detecting real defects.
18607273
X-tolerant test response compaction
Larger, denser designs lead to more defects; higher quality requirements and new test methods lead to an explosion in test data volume. Test compression technique attempt to do more testing with fewer bits. This article summarizes one such method, X compact which addresses how unknowns the bane of compression and logic BIST techniques are eliminated. DFT engineers must spend serious effort to minimize Xs in future designs. It is impossible to eliminate all Xs. X-tolerant response compactors are necessary for tolerating residual Xs to enable massive compaction with practically no impact on test quality. X-compactors are mainly useful for test compression purposes and provide up to 80 times the test response compaction of traditional scan. X-tolerant signature analyzers extend the X-compact concept to incorporate time compaction, thereby tolerating thousands of Xs and reducing test response data volume by 50 to 2,000 times relative to traditional scan. These signature analyzers are extremely beneficial for BIST because Xs can easily corrupt traditional MISR-based BIST signature analyzers. X-tolerant response compactors also enable efficient diagnosis essential to fast yield-learning.
2397835
Speed clustering of integrated circuits
Experimental data on 0.18 /spl mu/ test chips shows strong evidence of clustering of speeds of neighboring dies on a wafer. This clustering phenomenon is utilized to develop techniques for predicting the speed of a part from the speeds of three or more of its neighbors. On-chip processor monitors are used to further improve the prediction accuracy of these techniques. Experimental data demonstrates both the effectiveness of these prediction schemes and the possibility of applying of them to reduce the cost of speed binning.
900289
Techniques and algorithms for fault grading of FPGA interconnect test configurations
Conventional fault simulation techniques for field programmable gate arrays (FPGAs) are very complicated and time consuming. The alternative, FPGA fault emulation technique, is incomplete and can be used only after the FPGA chip is manufactured. In this paper, we present efficient algorithms for computing the fault coverage of a given FPGA test configuration. The faults considered are opens and shorts in FPGA interconnects. The presented technique is able to report all detectable and undetectable faults and, compared with conventional methods, is orders of magnitude faster.
2705949
Logic soft errors in sub-65nm technologies design and CAD challenges
Logic soft errors are radiation induced transient errors in sequential elements (flip-flops and latches) and combinational logic. Robust enterprise platforms in sub-65nm technologies require designs with built-in logic soft error protection. Effective logic soft error protection requires solutions to the following three problems: (1) accurate soft error rate estimation for combinational logic networks; (2) automated estimation of system effects of logic soft errors, and identification of regions in a design that must be protected; and, (3) new cost-effective techniques for logic soft error protection, because classical fault-tolerance techniques are very expensive.
2734062
A design diversity metric and reliability analysis for redundant systems
Design diversity has long been used to protect redundant systems against common-mode failures. The conventional notion of diversity relies on "independent" generation of "different" implementations. This concept is qualitative and does not provide a basis to compare the reliabilities of two diverse systems. In this paper, for the first time, we present a metric to quantify diversity among several designs. Based on this metric, we derive analytical reliability models that show a simple relationship between design diversity, system failure rate, and mission time. In addition, we present simulation results to demonstrate the effectiveness of design diversity in Duplex and Triple Modular Redundant (TMR) systems. For independent multiple-module failures, we show that, mere use of different implementations does not always guarantee higher reliability compared to redundant systems with identical implementations-it is important to analyze the reliability of redundant systems using our metric. For common-mode failures and design faults, there is a significant gain in using different implementations-however, as our analysis shows, the gain diminishes as the mission time increases. Our simulation results also demonstrate the usefulness of diversity for enhancing the self-testing properties of redundant systems.
8080205
Using Feature Combination and Statistical Resampling for Accurate Face Recognition Based on Frequency Domain Representation of Facial Asymmetry
This paper explores the efficiency of facial asymmetry in face identification tasks using a frequency domain representation. Satisfactory results are obtained for two different tasks, namely, human identification under extreme expression variations and expression classification, using a PCA-type classifier on a database with 55 individuals, which establishes the robustness of these measures to intra-personal distortions. Furthermore, we demonstrate that it is possible to improve upon these results significantly by simple means such as feature set combination and statistical resampling methods like bagging and random subspace method (RSM) using the same PCA-type base classifier. This even succeeds in attaining perfect classification results with 100% accuracy in some cases. Moreover, both these methods require few additional resources (computing time and power), hence they are useful for practical applications as well and help establish the effectiveness of frequency domain representation of facial asymmetry in automatic identification tasks
45280262
Leveraging information in multi-echelon inventory systems
Abstract Decision-making in multi-echelon inventory systems is often facilitated by the availability of information. In this paper, we examine the effect of utilising demand information in a one-warehouse two-retailer system operating under periodic-review. A common and fixed replenishment interval is assumed for all stages. The lead times are deterministic, and are small compared to the replenishment interval. The warehouse does not maintain any cycle stock, i.e., as soon as replenishment arrives at the warehouse, retailers’ demands are fulfilled from the available stock. In the event of a shortage at the warehouse, two cases have been considered––emergency shipment and allocation. For both the cases, expected total cost (ETC) models have been developed, and it has been shown through numerical examples that the optimal ETC in the presence of demand information is always lower than that in the absence of demand information. It is also noted that the order-up-to level at the warehouse has to be dynamic to reap the benefits of availability of demand information.
14971359
PVS Strategies for Proving Abstraction Properties of Automata
Abstractions are important in specifying and proving properties of complex systems. To prove that a given automaton implements an abstract specification automaton, one must first find the correct abstraction relation between the states of the automata, and then show that this relation is preserved by all corresponding action sequences of the two automata. This paper describes tool support based on the PVS theorem prover that can help users accomplish the second task, in other words, in proving a candidate abstraction relation correct. This tool support relies on a clean and uniform technique for defining abstraction properties relating automata that uses library theories for defining abstraction relations and templates for specifying automata and abstraction theorems. The paper then describes how the templates and theories allow development of generic, high level PVS strategies that aid in the mechanization of abstraction proofs. These strategies first set up the standard subgoals for the abstraction proofs and then execute the standard initial proof steps for these subgoals, thus making the process of proving abstraction properties in PVS more automated. With suitable supplementary strategies to implement the “natural” proof steps needed to complete the proofs of any of the standard subgoals remaining to be proved, the abstraction proof strategies can form part of a set of mechanized proof steps that can be used interactively to translate high level proof sketches into PVS proofs. Using timed I/O automata examples taken from the literature, this paper illustrates use of the templates, theories, and strategies described to specify and prove two types of abstraction property: refinement and forward simulation.
11380579
Bitmap indexes for large scientific data sets: a case study
The data used by today's scientific applications are often very high in dimensionality and staggering in size. These characteristics necessitate the use of a good multidimensional indexing strategy to provide efficient access to the data. Researchers have previously proposed the use of bitmap indexes for high-dimension scientific data as a way of overcoming the drawbacks of traditional multidimensional indexes such as R-trees and KD-trees, which are bulky and whose performance does not scale well as the number of dimensions increases. However, the techniques proposed in previous work on bitmap indexes are not sufficient to address all problems that arise in practice. In experiments with real datasets, we experienced problems with index size and query performance. To overcome these shortcomings, we propose the use of adaptive, multilevel, multi-resolution bitmap indexes, and evaluate their performance in two scientific domains. Our preliminary experiments with a parallel query processor and index creator also show that it is very easy to parallelize a bitmap index
10906898
The Role of Statistical Models in Biometric Authentication
The current paper demonstrates the role of statistical models in authentication tasks – both in system development and in performance evaluation. We first introduce a model-based face authentication system based on the Fourier domain phase using Gaussian Mixture Models (GMM) which yields verification error rates as low as 0.3% on a face database of 65 individuals with extreme illumination variations. We then present a statistical framework for predicting authentication error rates for future populations in a rigorous way. This is in contrast to most evaluation protocols used today that are based on observational studies and valid only for the databases at hand. Applications establish that our model-based approach has better predictive performance than an existing state-of-the-art authentication technique.