Cluster error correction and on-line repair for real-time TSV array

Tsung-Chu Huang
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Abstract

As a high-speed circuit-level real-time channel through-silicon vias admit only several levels of logic gates for correcting and repairing within a clock cycle. Unfortunately they are usually arranged as a crowded array for floorplanning and manufacturing reasons. To repair cluster faults and correct cluster errors, in this paper a complete strategy with a fast and adaptive architecture is proposed for built-in self-repairing, correcting and monitoring. The strategy includes off-line built-in self-test/repair and on-line correction, monitoring and repair. An LFSR-based noisy channel emulator is developed for verifying the architecture and evaluating the performance in a magnified probabilistic model. A conditional probability based cluster error model is also developed for analyzing the MTTR and BLER analyses posteriori to the AWGN noise. Evaluations prove that the proposed architecture can be effectively and efficiently suitable for hybrid memory cube to test, repair, detect, correct and monitor a large cluster error almost within a nano-second.
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实时TSV阵列的聚类纠错与在线修复
作为一种高速电路级实时通道,硅通孔在一个时钟周期内只允许几个级别的逻辑门进行校正和修复。不幸的是,由于地板规划和制造原因,它们通常被安排成一个拥挤的阵列。为了修复集群故障和纠正集群错误,本文提出了一种具有快速、自适应架构的集群内嵌自修复、纠错和监控的完整策略。该策略包括离线内置自测/修复和在线校正、监测和修复。开发了基于lfsr的噪声信道仿真器,在放大概率模型下验证了该结构并评估了其性能。本文还建立了一种基于条件概率的聚类误差模型,用于分析MTTR和BLER对AWGN噪声的后验分析。实验结果表明,该架构可以有效地适用于混合存储立方体,在纳秒内完成大规模集群错误的测试、修复、检测、纠正和监控。
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