Hierarchical Memory Diagnosis
Guilherme Cardoso Medeiros (TU Delft - Quantum & Computer Engineering)
M.C.R. Fieback (TU Delft - Computer Engineering)
A.B. Gebregiorgis (TU Delft - Computer Engineering)
Mottaqiallah Taouil (TU Delft - Computer Engineering)
L.M. Poehls (RWTH Aachen University)
Said Hamdioui (TU Delft - Quantum & Computer Engineering)
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Abstract
High-quality memory diagnosis methodologies are critical enablers for scaled memory devices as they reduce time to market and provide valuable information regarding test escapes and customer returns. This paper presents an efficient Hierarchical Memory Diagnosis (HMD) approach that accurately diagnoses faults in the entire memory. Faults are diagnosed hierarchically; first, their location, then their nature (i.e., static or dynamic), and finally, their functional fault model. The HMD approach leads to a more accurate diagnostic, enabling the precise identification of yield loss causes.