Testability and redundancy techniques for improved yield and reliability of CMOS VLSI circuits

The research presented in this thesis is concerned with the design of fault-tolerant integrated circuits as a contribution to the design of fault-tolerant systems. The economical manufacture of very large area ICs will necessitate the incorporation of fault-tolerance features which are routinely employed in current high density dynamic random access memories. Furthermore, the growing use of ICs in safety-critical applications and/or hostile environments in addition to the prospect of single-chip systems will mandate the use of fault-tolerance for improved reliability. A fault-tolerant IC must be able to detect and correct all possible faults that may affect its operation. The ability of a chip to detect its own faults is not only necessary for fault-tolerance, but it is also regarded as the ultimate solution to the problem of testing. Off-line periodic testing is selected for this research because it achieves better coverage of physical faults and it requires less extra hardware than on-line error detection techniques. Tests for CMOS stuck-open faults are shown to detect all other faults. Simple test sequence generation procedures for the detection of all faults are derived. The test sequences generated by these procedures produce a trivial output, thereby, greatly simplifying the task of test response analysis. A further advantage of the proposed test generation procedures is that they do not require the enumeration of faults. The implementation of built-in self-test is considered and it is shown that the hardware overhead is comparable to that associated with pseudo-random and pseudo-exhaustive techniques while achieving a much higher fault coverage through-the use of the proposed test generation procedures. The consideration of the problem of testing the test circuitry led to the conclusion that complete test coverage may be achieved if separate chips cooperate in testing each other's untested parts. An alternative approach towards complete test coverage would be to design the test circuitry so that it is as distributed as possible and so that it is tested as it performs its function. Fault correction relies on the provision of spare units and a means of reconfiguring the circuit so that the faulty units are discarded. This raises the question of what is the optimum size of a unit? A mathematical model, linking yield and reliability is therefore developed to answer such a question and also to study the effects of such parameters as the amount of redundancy, the size of the additional circuitry required for testing and reconfiguration, and the effect of periodic testing on reliability. The stringent requirement on the size of the reconfiguration logic is illustrated by the application of the model to a typical example. Another important result concerns the effect of periodic testing on reliability. It is shown that periodic off-line testing can achieve approximately the same level of reliability as on-line testing, even when the time between tests is many hundreds of hours

Parallel Architectures for Planetary Exploration Requirements (PAPER)

The Parallel Architectures for Planetary Exploration Requirements (PAPER) project is essentially research oriented towards technology insertion issues for NASA's unmanned planetary probes. It was initiated to complement and augment the long-term efforts for space exploration with particular reference to NASA/LaRC's (NASA Langley Research Center) research needs for planetary exploration missions of the mid and late 1990s. The requirements for space missions as given in the somewhat dated Advanced Information Processing Systems (AIPS) requirements document are contrasted with the new requirements from JPL/Caltech involving sensor data capture and scene analysis. It is shown that more stringent requirements have arisen as a result of technological advancements. Two possible architectures, the AIPS Proof of Concept (POC) configuration and the MAX Fault-tolerant dataflow multiprocessor, were evaluated. The main observation was that the AIPS design is biased towards fault tolerance and may not be an ideal architecture for planetary and deep space probes due to high cost and complexity. The MAX concepts appears to be a promising candidate, except that more detailed information is required. The feasibility for adding neural computation capability to this architecture needs to be studied. Key impact issues for architectural design of computing systems meant for planetary missions were also identified

Fault-tolerant hardware designs and their reliability analysis

This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University.Fault-tolerance, which is a complement to fault prevention, is an effective method of achieving ultra-high reliability. By taking this approach fault free computation can be achieved despite the presence of fault in the system. In this thesis three new fault tolerant techniques are presented and their advantages over well known fault-tolerant strategies are shown. One of these new techniques achieves higher reliability than any other similar techniques presented in the literature. Generally fault-tolerant structures consist of four major blocks: the replicated modules, the disagreement and detection circuit, the switching circuit, and the voting mechanism. The most critical component in a fault-tolerant system is the voter because the final output of the system is computed by this component. This dissertation presents a new implementation for voters which reduces both the complexity and the occupied area on the chip. The structures of the three techniques developed in this work are such that the complexity of their switching mechanisms grows only linearly with the number of modules but the voting mechanism complexity increases significantly. This is a better approach than those schemes in which the switching complexity increases significantly and the voter's complexity remains constant or grows linearly with the number of modules because it is easier to implement a complex voter than a complex switch (voters have more regular structures). Extensive comparisons are made between different fault-tolerant techniques. A new reliability model is also developed for system reliability evaluation of the new designs. The results of these analyses are plotted, and the advantages of the new techniques are demonstrated. In the final part of the work an expert system is described which uses the knowledge acquired by these comparisons. This expert system is meant as a prototype of a component of a CAD tool which will act as an advisor on fault-tolerant techniques

Autonomously Reconfigurable Artificial Neural Network on a Chip

Artificial neural network (ANN), an established bio-inspired computing paradigm, has proved very effective in a variety of real-world problems and particularly useful for various emerging biomedical applications using specialized ANN hardware. Unfortunately, these ANN-based systems are increasingly vulnerable to both transient and permanent faults due to unrelenting advances in CMOS technology scaling, which sometimes can be catastrophic. The considerable resource and energy consumption and the lack of dynamic adaptability make conventional fault-tolerant techniques unsuitable for future portable medical solutions. Inspired by the self-healing and self-recovery mechanisms of human nervous system, this research seeks to address reliability issues of ANN-based hardware by proposing an Autonomously Reconfigurable Artificial Neural Network (ARANN) architectural framework. Leveraging the homogeneous structural characteristics of neural networks, ARANN is capable of adapting its structures and operations, both algorithmically and microarchitecturally, to react to unexpected neuron failures. Specifically, we propose three key techniques --- Distributed ANN, Decoupled Virtual-to-Physical Neuron Mapping, and Dual-Layer Synchronization --- to achieve cost-effective structural adaptation and ensure accurate system recovery. Moreover, an ARANN-enabled self-optimizing workflow is presented to adaptively explore a "Pareto-optimal" neural network structure for a given application, on the fly. Implemented and demonstrated on a Virtex-5 FPGA, ARANN can cover and adapt 93% chip area (neurons) with less than 1% chip overhead and O(n) reconfiguration latency. A detailed performance analysis has been completed based on various recovery scenarios

Interconnect yield analysis and fault tolerance for field programmable gate arrays

Imperial Users onl

Analysis and design of algorithm-based fault-tolerant systems

An important consideration in the design of high performance multiprocessor systems is to ensure the correctness of the results computed in the presence of transient and intermittent failures. Concurrent error detection and correction have been applied to such systems in order to achieve reliability. Algorithm Based Fault Tolerance (ABFT) was suggested as a cost-effective concurrent error detection scheme. The research was motivated by the complexity involved in the analysis and design of ABFT systems. To that end, a matrix-based model was developed and, based on that, algorithms for both the design and analysis of ABFT systems are formulated. These algorithms are less complex than the existing ones. In order to reduce the complexity further, a hierarchical approach is developed for the analysis of large systems

The Fifth NASA Symposium on VLSI Design

The fifth annual NASA Symposium on VLSI Design had 13 sessions including Radiation Effects, Architectures, Mixed Signal, Design Techniques, Fault Testing, Synthesis, Signal Processing, and other Featured Presentations. The symposium provides insights into developments in VLSI and digital systems which can be used to increase data systems performance. The presentations share insights into next generation advances that will serve as a basis for future VLSI design