Paper

EPIC: Efficient prediction of IC manufacturing hotspots with a unified meta-classification formulation

Publication Date:
Publication Date
March 2012
Author(s)
Duo Ding, Bei Yu, J. Ghosh and D. Z. Pan

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Abstract

Iddq testing has been a critical integral component in test suites for screening unreliable devices. As the silicon technology keeps shrinking, Iddq values and their variation increase as well. Moreover, along with rapid design scaling, defect-induced leakage currents become less significant when compared to full-chip current and also make themselves less distinguishable. Traditional Iddq methods become less effective and cause more test escapes and yield loss. Therefore, in this paper, a new test method named σ-Iddq testing is proposed and integrates (1) a variation-aware full-chip leakage estimator and (2) a clustering algorithm to classify chip without using threshold values. Experimental result shows that σ-Iddq testing achieves a higher classification accuracy in a 45 nm technology when compared to a single-threshold Iddq testing. As a result, both the process-variation and design-scaling impacts are successfully excluded and thus the defective chips can be identified intelligently.