5916562
Testing digital circuits with constraints
Many digital circuits have constraints on the logic values a set of signal lines can have. In this paper, we present two new techniques for detecting the illegal combinations of logic values in digital circuits and two techniques for preventing them from damaging the circuit or corrupting the test results. The hardware overhead of our technique is minimal and imposes negligible delay overhead. Simulation results show that the area overhead of our techniques is less than 1%. Unlike previous techniques, the fault coverage of the legal test patterns in a given test set is not sacrificed with our techniques. Furthermore, our techniques are applicable during IC production test, BIST, board-level tests and system-level tests.
15807495
Application-independent testing of FPGA interconnects
We present a new automatic test-configuration-generation technique for application-independent manufacturing testing of the interconnection network of static-random-access-memory-based field programmable gate arrays (FPGAs). This technique targets detection of open and bridging faults in the wiring channels and programmable switches in the interconnects. Experimental results on Xilinx Virtex FPGAs show that very few test configurations are required to cover stuck-open, stuck-closed, open, and bridging faults in the interconnects.
42903241
Test vector compression using EDA-ATE synergies
This paper presents a new test vector compression technique, which utilizes synergies between Automatic Test Pattern Generation (ATPG) tools provided by EDA (Electronic Design Automation) vendors and Automatic Test Equipment (ATE). The basic approach is to achieve significant compression by agreeing between ATE and ATPG on how to fill don't care values in the test vectors such that these bits need not be stored on ATE and also possibly not communicated to DUT if decompression is done on chip. Our new technique allows sub-vector level fine grained mixing of pseudo-randomly generated bits and ATPG generated bits. Experimental results, on an actual industrial network processor design, show a compression ratio of about 17x.
41662557
Soft Errors: Technology Trends, System Effects, and Protection Techniques
Radiation-induced soft errors are getting worse in digital systems manufactured in advanced technologies. Stringent data integrity and availability requirements of enterprise computing and networking applications demand special attention to soft errors in sequential elements and combinational logic. This tutorial will discuss the impact of technology scaling on soft error rates, circuit-level modeling of soft errors, architectural impact of soft errors, challenges associated with evaluation of run-time behaviors of systems in the presence of soft errors, actual data on system behaviors in the presence of soft errors, metrics for quantifying soft error vulnerabilities, design of architectures with Built-in-Soft-Error-Resilience techniques, and actual case studies.
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.
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.
29308229
Safety Verification of Model Helicopter Controller Using Hybrid Input/Output Automata
This paper presents an application of the Hybrid I/O Automaton (HIOA) framework [12] in verifying a realistic hybrid system. A supervisory pitch controller for a model helicopter system is designed and then verified. The design of the supervisor is limited by the actuator bandwidth, the sensor inaccuracies, and the sampling rates. Verification is carried out by induction over the length of an execution of the composed system automaton. The HIOA model makes the inductive proofs tractable by decomposing them into independent discrete and continuous parts. The paper also presents a set of language constructs for specifying hybrid I/O automata.
13253511
Verifying Average Dwell Time by Solving Optimization Problems
A switched system is a hybrid system whose discrete mechanisms are abstracted away in terms of an exogenous switching signal which brings about the mode switches. For switched systems, the Average Dwell time (ADT) property defines restricted classes of switching signals which can be used for proving stability. In this paper, we develop optimization-based methods for automatically verifying ADT properties of hybrid systems. This enables us to prove stability of hybrid systems, provided the individual modes of the system are stable. For two special classes of hybrid systems, we show that the resulting optimization problems can indeed be solved efficiently using standard mathematical programming techniques. We also present simulation relation-based proof methods for establishing equivalence of hybrid systems with respect to ADT. The proposed methods are applied to verify ADT properties of a linear hysteresis switch and a nondeterministic thermostat.
1899140
Learning Cycle-Linear Hybrid Automata for Excitable Cells
We show how to automatically learn the class of Hybrid Automata called Cycle-Linear Hybrid Automata (CLHA) in order to model the behavior of excitable cells. Such cells, whose main purpose is to amplify and propagate an electrical signal known as the action potential (AP), serve as the "biologic transistors" of living organisms. The learning algorithm we propose comprises the following three phases: (1) Geometric analysis of the APs in the training set is used to identify, for each AP, the modes and switching logic of the corresponding Linear Hybrid Automata. (2) For each mode, the modified Prony's method is used to learn the coefficients of the associated linear flows. (3) The modified Prony's method is used again to learn the functions that adjust, on a per-cycle basis, the mode dynamics and switching logic of the Linear Hybrid Automata obtained in the first two phases. Our results show that the learned CLHA is able to successfully capture AP morphology and other important excitable-cell properties, such as refractoriness and restitution, up to a prescribed approximation error. Our approach is fully implemented in MATLAB and, to the best of our knowledge, provides the most accurate approximation model for ECs to date.
35096806
Human Face Identification from Video Based on Frequency Domain Asymmetry Representation Using Hidden Markov Models
In this paper we introduce a novel human face identification scheme from video data based on a frequency domain representation of facial asymmetry. A Hidden Markov Model (HMM) is used to learn the temporal dynamics of the training video sequences of each subject and classification of the test video sequences is performed using the likelihood scores obtained from the HMMs. We apply this method to a video database containing 55 subjects showing extreme expression variations and demonstrate that the HMM-based method performs much better than identification based on the still images using an Individual PCA (IPCA) classifier, achieving more than 30% improvement.
35384166
Facial asymmetry quantification for expression invariant human identification
We investigate facial asymmetry as a biometric under expression variation. For the first time, we have defined two types of quantified facial asymmetry measures that are easily computable from facial images and videos. Our findings show that the asymmetry measures of automatically selected facial regions capture individual differences that are relatively stable to facial expression variations. More importantly, a synergy is achieved by combining facial asymmetry information with conventional EigenFace and FisherFace methods. We have assessed the generality of these findings across two publicly available face databases: Using a random subset of 110 subjects from the FERET database, a 38% classification error reduction rate is obtained. Error reduction rates of 45-100% are achieved on 55 subjects from the Cohn-Kanade AU-Coded Facial Expression Database. These results suggest that facial asymmetry may provide complementary discriminative information to human identification methods, which has been missing in automatic human identification.