An efficient logic fault diagnosis framework based on effect-cause approach

Fault diagnosis plays an important role in improving the circuit design process and the manufacturing yield. With the increasing number of gates in modern circuits, determining the source of failure in a defective circuit is becoming more and more challenging. In this research, we present an efficient effect-cause diagnosis framework for combinational VLSI circuits. The framework consists of three stages to obtain an accurate and reasonably precise diagnosis. First, an improved critical path tracing algorithm is proposed to identify an initial suspect list by backtracing from faulty primary outputs toward primary inputs. Compared to the traditional critical path tracing approach, our algorithm is faster and exact. Second, a novel probabilistic ranking model is applied to rank the suspects so that the most suspicious one will be ranked at or near the top. Several fast filtering methods are used to prune unrelated suspects. Finally, to refine the diagnosis, fault simulation is performed on the top suspect nets using several common fault models. The difference between the observed faulty behavior and the simulated behavior is used to rank each suspect. Experimental results on ISCAS85 benchmark circuits show that this diagnosis approach is efficient both in terms of memory space and CPU time and the diagnosis results are accurate and reasonably precise

Exploring the Mysteries of System-Level Test

System-level test, or SLT, is an increasingly important process step in today's integrated circuit testing flows. Broadly speaking, SLT aims at executing functional workloads in operational modes. In this paper, we consolidate available knowledge about what SLT is precisely and why it is used despite its considerable costs and complexities. We discuss the types or failures covered by SLT, and outline approaches to quality assessment, test generation and root-cause diagnosis in the context of SLT. Observing that the theoretical understanding for all these questions has not yet reached the level of maturity of the more conventional structural and functional test methods, we outline new and promising directions for methodical developments leveraging on recent findings from software engineering.Comment: 7 pages, 2 figure

Third Yearly Activity Report

The calculation work performed during the 3rd project year in WP2 as well as the R&D activities carried out in WP3, WP4 and WP5 are described in this report. In addition, the work dedicated to the project management (WP1) as well as to WP6 regarding the dissemination/communication activities and the education/training program (e.g. the follow-up of the mobility program between different organizations in the consortium, training on simulation tools and activities accomplished by PhD/post-doctoral students) is also reported

Experimental analysis of computer system dependability

This paper reviews an area which has evolved over the past 15 years: experimental analysis of computer system dependability. Methodologies and advances are discussed for three basic approaches used in the area: simulated fault injection, physical fault injection, and measurement-based analysis. The three approaches are suited, respectively, to dependability evaluation in the three phases of a system's life: design phase, prototype phase, and operational phase. Before the discussion of these phases, several statistical techniques used in the area are introduced. For each phase, a classification of research methods or study topics is outlined, followed by discussion of these methods or topics as well as representative studies. The statistical techniques introduced include the estimation of parameters and confidence intervals, probability distribution characterization, and several multivariate analysis methods. Importance sampling, a statistical technique used to accelerate Monte Carlo simulation, is also introduced. The discussion of simulated fault injection covers electrical-level, logic-level, and function-level fault injection methods as well as representative simulation environments such as FOCUS and DEPEND. The discussion of physical fault injection covers hardware, software, and radiation fault injection methods as well as several software and hybrid tools including FIAT, FERARI, HYBRID, and FINE. The discussion of measurement-based analysis covers measurement and data processing techniques, basic error characterization, dependency analysis, Markov reward modeling, software-dependability, and fault diagnosis. The discussion involves several important issues studies in the area, including fault models, fast simulation techniques, workload/failure dependency, correlated failures, and software fault tolerance

Reliable Low-Latency and Low-Complexity Viterbi Architectures Benchmarked on ASIC and FPGA

The Viterbi algorithm is commonly applied in a number of sensitive usage models including decoding convolutional codes used in communications such as satellite communication, cellular relay, and wireless local area networks. Moreover, the algorithm has been applied to automatic speech recognition and storage devices. In this thesis, efficient error detection schemes for architectures based on low-latency, low-complexity Viterbi decoders are presented. The merit of the proposed schemes is that reliability requirements, overhead tolerance, and performance degradation limits are embedded in the structures and can be adapted accordingly. We also present three variants of recomputing with encoded operands and its modifications to detect both transient and permanent faults, coupled with signature-based schemes. The instrumented decoder architecture has been subjected to extensive error detection assessments through simulations, and application-specific integrated circuit (ASIC) [32nm library] and field-programmable gate array (FPGA) [Xilinx Virtex-6 family] implementations for benchmark. The proposed fine-grained approaches can be utilized based on reliability objectives and performance/implementation metrics degradation tolerance

Neural Dynamics of Autistic Behaviors: Cognitive, Emotional, and Timing Substrates

What brain mechanisms underlie autism and how do they give rise to autistic behavioral symptoms? This article describes a neural model, called the iSTART model, which proposes how cognitive, emotional, timing, and motor processes may interact together to create and perpetuate autistic symptoms. These model processes were originally developed to explain data concerning how the brain controls normal behaviors. The iSTART model shows how autistic behavioral symptoms may arise from prescribed breakdowns in these brain processes.Air Force Office of Scientific Research (F49620-01-1-0397); Office of Naval Research (N00014-01-1-0624

A phenotypic and molecular characterization of the fmr1-tm1Cgr Fragile X mouse

Fragile X Syndrome is the most common form of\ud inherited mental retardation. It is also known for having\ud a substantial behavioral morbidity, including autistic features. In humans, Fragile X Syndrome is almost always\ud caused by inactivation of the X-linked FMR1 gene. A\ud single knockout mouse model, fmr1-tm1Cgr, exists. In\ud this report we further characterize the cognitive and\ud behavioral phenotype of the fmr1-tm1Cgr Fragile X\ud mouse through the use of F1 hybrid mice derived from\ud two inbred strains (FVB/NJ and C57BL/6J). Use of F1\ud hybrids allows focus on the effects of the fmr1-tm1Cgr\ud allele with reduced influence from recessive alleles\ud present in the parental inbred strains. We find that the\ud cognitive phenotype of fmr1-tm1Cgr mice, including\ud measures of working memory and learning set formation\ud that are known to be seriously impacted in humans with\ud Fragile X Syndrome, are essentially normal. Further testing of inbred strains supports this conclusion. Thus, any\ud fmr1-tm1Cgr cognitive deficit is surprisingly mild or\ud absent. There is, however, clear support presented for a\ud robust audiogenic seizure phenotype in all strains tested,\ud as well as increased entries into the center of an open\ud field. Finally, a molecular examination of the fmr1-tm1Cgr\ud mouse shows that, contrary to common belief, it is not a\ud molecular null. Implications of this finding for interpretation of the phenotype are discussed.\u