Detection of hard faults in combinational logic circuits

ABSTRACT: Previous Work in identifying hard to test faults (HFs) -- The effect of reconvergent fanout and redundancy -- Testability measures (TMs)Using of ATPGs to detect HFs -- Previous use of cost in Testability analysis -- Review of automatic test pattern generation (ATPG) -- Fault modelling -- Single versus multiple path sensitization -- The four ATPG phases of deterministic gate level test generation -- Random test pattern generation and hybrid methods -- Review of the fan algorithm -- Backtrack reduction methods and the importance of heuristics -- Mixed graph -- binary decision diagram (GBDD) circuit model -- A review of graph techniques -- A review of binary decisions diagrams (BDDs) techniques -- gBDD -- graph binary decision diagrams -- Detection of hard faults using HUB -- Introduction to budgetary constraints -- The HUB algorithm -- Important HUB attributes -- Circuits characteristics of used for results -- Comparison of gBDD -- ATPG related results -- Fault simulation related results -- Hard fault detection

Cross-Layer Optimization for Power-Efficient and Robust Digital Circuits and Systems

With the increasing digital services demand, performance and power-efficiency become vital requirements for digital circuits and systems. However, the enabling CMOS technology scaling has been facing significant challenges of device uncertainties, such as process, voltage, and temperature variations. To ensure system reliability, worst-case corner assumptions are usually made in each design level. However, the over-pessimistic worst-case margin leads to unnecessary power waste and performance loss as high as 2.2x. Since optimizations are traditionally confined to each specific level, those safe margins can hardly be properly exploited. To tackle the challenge, it is therefore advised in this Ph.D. thesis to perform a cross-layer optimization for digital signal processing circuits and systems, to achieve a global balance of power consumption and output quality. To conclude, the traditional over-pessimistic worst-case approach leads to huge power waste. In contrast, the adaptive voltage scaling approach saves power (25% for the CORDIC application) by providing a just-needed supply voltage. The power saving is maximized (46% for CORDIC) when a more aggressive voltage over-scaling scheme is applied. These sparsely occurred circuit errors produced by aggressive voltage over-scaling are mitigated by higher level error resilient designs. For functions like FFT and CORDIC, smart error mitigation schemes were proposed to enhance reliability (soft-errors and timing-errors, respectively). Applications like Massive MIMO systems are robust against lower level errors, thanks to the intrinsically redundant antennas. This property makes it applicable to embrace digital hardware that trades quality for power savings.Comment: 190 page