On generating optimal signal probabilities for random tests: a genetic approach

Genetic Algorithms are robust search and optimization techniques. A Genetic Algorithm based approach for determining the optimal input distributions for generating random test vectors is proposed in the paper. A cost function based on the COP testability measure for determining the efficacy of the input distributions is discussed. A brief overview of Genetic Algorithms (GAs) and the specific details of our implementation are described. Experimental results based on ISCAS-85 benchmark circuits are presented. The performance of our GAbased approach is compared with previous results. While the GA generates more efficient input distributions than the previous methods which are based on gradient descent search, the overheads of the GA in computing the input distributions are larger. To account for the relatively quick convergence of the gradient descent methods, we analyze the landscape of the COP-based cost function. We prove that the cost function is unimodal in the search space. This feature makes the cost function amenable to optimization by gradient-descent techniques as compared to random search methods such as Genetic Algorithms

Ensuring a High Quality Digital Device through Design for Testability

An electronic device is reliable if it is available for use most of the times throughout its life. The reliability can be affected by mishandling and use under abnormal operating conditions. High quality product cannot be achieved without proper verification and testing during the product development cycle. If the design is difficult to test, then it is very likely that most of the faults will not be detected before it is shipped to the customer. This paper describes how product quality can be improved by making the hardware design testable. Various designs for testability techniqueswere discussed. A three bit counter circuit was used to illustrate the benefits of design for testability by using scan chain methodology

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

A survey of an introduction to fault diagnosis algorithms

This report surveys the field of diagnosis and introduces some of the key algorithms and heuristics currently in use. Fault diagnosis is an important and a rapidly growing discipline. This is important in the design of self-repairable computers because the present diagnosis resolution of its fault-tolerant computer is limited to a functional unit or processor. Better resolution is necessary before failed units can become partially reuseable. The approach that holds the greatest promise is that of resident microdiagnostics; however, that presupposes a microprogrammable architecture for the computer being self-diagnosed. The presentation is tutorial and contains examples. An extensive bibliography of some 220 entries is included

Real Time Fault Detection and Diagnostics Using FPGA-Based Architecture

Errors within circuits caused by radiation continue to be an important concern to developers. A new methodology of real time fault detection and diagnostics utilizing FPGA based architectures while under radiation were investigated in this research. The contributions of this research are focused on three areas; a full test platform to evaluate a circuit while under irradiation, an algorithm to detect and diagnose fault locations within a circuit, and finally to characterize Triple Design Triple Modular Redundancy (TDTMR), a new form of TMR. Five different test setups, injected fault test, gamma radiation test, thermal radiation test, optical laser test, and optical flash test, were used to assess the effectiveness of these three research goals. The testing platform was constructed with two FPGA boards, the Device Under Test (DUT) and the controller board, to generate and evaluate specific vector sets sent to the DUT. The testing platform combines a myriad of testing and measuring equipment and work hours onto one small reprogrammable and reusable FPGA. This device was able to be used in multiple test setups. The controlling logic can be interchanged to test multiple circuit designs under various forms of radiation. The detection and diagnostic algorithm was designed to determine fault locations in real time. The algorithm used for diagnosing the fault location uses inverse deductive elimination. By using test generation tools, fault lists were developed. The fault lists were used to narrow \ the possible fault locations within the circuit. The algorithm is able to detect single stuck at faults based on these lists. The algorithm can also detect multiple output errors but not able to diagnose multiple stuck at faults in real time

Functional testing of faults in asynchronous crossbar architecture

The challenge of extending Moore\u27s Law past the physical limits of the present semiconductor technology calls for novel innovations. Several novel nanotechnologies are being proposed as an alternative to their CMOS counterparts, with nanowire crossbar being one of the most promising paradigms. Quite recently, a new promising clock-free architecture, called the Asynchronous Crossbar Architecture has been proposed to enhance the manufacturability and to improve the robustness of digital circuits by removing various timing related failure modes. Even though the proposed clock-free architecture offers several merits, it is not free from the high defect rates induced due to nondeterministic nanoscale assembly. In this work, a unique Functional Test Algorithm (FTA) has been proposed and validated to test for manufacturing defects in this architecture. The proposed Functional Test Algorithm is aimed at reducing the testing overhead in terms of the time and space complexity associated with the existing sequential test scheme. In addition, it is designed to provide high fault coverage and excellent fault-tolerance via post-reconfiguration. This test scheme can be effectively used to assure true functionality of any threshold gate realized on a given PGMB. The main motivation behind this research is to propose a comprehensive test scheme which can achieve sufficiently high test coverage with acceptable test overhead. This test algorithm is a significant effort towards viable nanoscale computation --Abstract, page iv

Techniques for the realization of ultra- reliable spaceborne computer Final report

Bibliography and new techniques for use of error correction and redundancy to improve reliability of spaceborne computer