基于连续波785nm激光诱导故障分析(LIFA)的按需位级SRAM验证

Keith A. Serrels, Kris Dickson, Clifford Howard, Jose Garcia, Eric Foote, Gary Clark, Ben Gonzalez, Chinemerem Nwokolo
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引用次数: 0

摘要

利用连续波(CW) 785nm激光诱导故障分析(LIFA)系统,首次进行了按需位级静态随机存取存储器(SRAM)验证和隔离的实验演示。通过仔细的测试模式编辑和简单的通过/失败标志的观察,使用相关单元确定了在40nm, 16nm和5nm SRAM阵列中预选位的物理位置的空间映射能力。这项工作展示了一种新颖高效的快速位级逻辑到物理识别方法。与传统的位图验证方法(BKM)相比,它还提高了定位效率,后者通常依赖于故障后的光电显微镜(PEM)和/或在实际故障单元上执行的软缺陷定位/激光辅助设备更改(LADA)。这项新技术重新定义了SRAM位图验证和定位的最新技术,并为产品位图确认和随后的根本原因识别提供了一条显著改善周期时间的途径。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
On Demand Bit-Level SRAM Validation using CW 785nm Laser-Induced Fault Analysis (LIFA)
Abstract We present the first experimental demonstration of on demand bit-level Static Random Access Memory (SRAM) validation and isolation through the exploitation of a continuous wave (CW) 785nm Laser-Induced Fault Analysis (LIFA) system. Through careful test pattern edits and the observation of a simple pass/fail flag, the ability to spatially map the physical location of pre-selected bits in 40nm, 16nm, and 5nm SRAM arrays using correlation units is confirmed. This work demonstrates a novel and highly-efficient methodology for rapid bit-level logical-to-physical identification. It also improves localization efficacy over conventional bitmap validation best-known methods (BKM) which typically rely on post-fail Photo-Emission Microscopy (PEM) and/or Soft Defect Localization / Laser-Assisted Device Alteration (LADA) performed on an actual fail unit. This new technique re-defines the state-of-the-art in SRAM bitmap validation and localization and offers a pathway to significantly improve cycle time for both product bitmap qualification and subsequent root cause identification.
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