Screening small-delay defects using inter-path correlation to reduce reliability risk

Garcia-Gervacio, Jose L.; Nocua, Alejandro; Champac, Victor

doi:10.1016/j.microrel.2015.03.007

Cited by 3 publications

(2 citation statements)

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“…As mentioned before, process-induced variation should be distinguished from physical weak defects [13] uses output delay correlation of two logic paths, which is called inter-paths information to screen out SDFs and distinguish them from process variations. It exploits the fact that delay measurements for a pair of paths must agree with their interpath correlation.…”

Section: State Of the Artmentioning

confidence: 99%

“…Yet, a slow circuit due to variations may be safe whereas a slow circuit due to resistive weak defects may form a reliability threat. Distinguishing cells slow due to variations from defective cells has been the subject of ongoing research [10,[12][13][14] and [15]. A severe limitation of the previous works comes with the fact, that the defective cells are subject to variations too.…”

Section: Introductionmentioning

confidence: 99%

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Identifying Resistive Open Defects in Embedded Cells under Variations

Najafi-Haghi

Wunderlich

2023

J Electron Test

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Small Delay Faults (SDFs) due to weak defects and marginalities have to be distinguished from extra delays due to process variations, since they may form a reliability threat even if the resulting timing is within the specification. In this paper, it is shown that these faults can still be identified, even if the corresponding defect cell is deeply embedded into a combinational circuit and its observability is restricted. The results of a few delay tests at different voltages and frequencies serve as the input to machine learning procedures which can classify a circuit as marginal due to defects or just slow due to variations. Several machine learning techniques are investigated and compared with respect to accuracy, precision, and recall for different circuit sizes and defect scales. The classification strategies are powerful enough to sort out defective devices without a major impact on yield.

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Section: State Of the Artmentioning

confidence: 99%