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An On-Line Aging Detection and Tolerance Framework for Improving Reliability of STT-MRAMs
會議論文集

An On-Line Aging Detection and Tolerance Framework for Improving Reliability of STT-MRAMs

Yu-Guang Chen, Po-Yeh Huang 和 Jin-Fu Li
Proceedings of the 28th Asia and South Pacific Design Automation Conference, 頁碼.13-18
ACM Conferences
ASPDAC '23: 28th Asia and South Pacific Design Automation Conference
16/01/2023
Web of Science ID: WOS:000981940000003

摘要

Hardware Hardware -- Emerging technologies Hardware -- Emerging technologies -- Spintronics and magnetic technologies Hardware -- Hardware test Hardware -- Hardware test -- Memory test and repair Hardware -- Integrated circuits Hardware -- Integrated circuits -- Semiconductor memory Hardware -- Integrated circuits -- Semiconductor memory -- Dynamic memory Hardware -- Integrated circuits -- Semiconductor memory -- Non-volatile memory Hardware -- Integrated circuits -- Semiconductor memory -- Static memory Hardware -- Robustness
Spin-transfer-torque magnetic random-access memory (STT-MRAM) is one of the most promising emerging memories for on-chip memory. However, the magnetic tunnel junction (MTJ) in the STT-MRAM suffers from several reliability threats which degrade the endurance, create defects, and cause memory failure. One of the primary reliability issues comes from time-dependent dielectric breakdown (TDDB) on MTJ, which deviates resistance value of MTJ over time and may lead to reading error. To overcome this challenge, in this paper we present an on-line aging detection and tolerance framework to dynamically monitor the electrical parameter deviations and provide appropriate compensation to avoid reading error. The on-line aging detection mechanism can identify aged words by monitoring read current and then the aging tolerance mechanism can adjust the reference resistance of the sensing amplifier to compensate the aging-induced resistance drop of MTJ. In comparison with existing testing-based aging detection techniques, our mechanism can operate on-line with read operations for both aging detection and tolerance simultaneously with negligible performance overhead. Simulation and analysis results show that the proposed techniques can successfully detect 99% aging words under process variation and achieve at most 25% reliability improvement of STT-MRAMs.

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