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Efficient Repair Analysis Algorithm Exploration for Memory With Redundancy and In-Memory ECC

机译:冗余和内存中记忆的高效修复分析算法探索

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摘要

In-memory error correction code (ECC) is a promising technique to improve the yield and reliability of high density memory design. However, the use of in-memory ECC poses a new problem to memory repair analysis algorithm, which has not been explored before. This article first makes a quantitative evaluation and demonstrates that the straightforward algorithms for memory with redundancy and in-memory ECC have serious deficiency on either repair rate or repair analysis speed. Accordingly, an optimal repair analysis algorithm that leverages preprocessing/filter algorithms, hybrid search tree, and depth-first search strategy is proposed to achieve low computational complexity and optimal repair rate in the meantime. In addition, a heuristic repair analysis algorithm that uses a greedy strategy is proposed to efficiently find repair solutions. Experimental results demonstrate that the proposed optimal repair analysis algorithm can achieve optimal repair rate and increase the repair analysis speed by up to 10(5) x compared with the straightforward exhaustive search algorithm. The proposed heuristic repair analysis algorithm is approximately 28 percent faster than the proposed optimal algorithm, at the expense of 5.8 percent repair rate loss.
机译:内存纠错码(ECC)是提高高密度存储器设计的产量和可靠性的有希望的技术。然而,使用内部ECC对存储器修复分析算法构成了新问题,这尚未探讨。本文首先进行了定量评估,并证明了具有冗余和内部ECC的内存的直接算法对维修率或修复分析速度具有严重缺陷。因此,提出了一种利用预处理/滤波算法,混合搜索树和深度第一搜索策略的最佳修复分析算法,以实现低计算复杂性和相同的修复率。此外,提出了一种使用贪婪策略的启发式修复分析算法,以有效地找到修复解决方案。实验结果表明,与直接详尽的搜索算法相比,所提出的最佳修复分析算法可以实现最佳的修复速率,并将修复分析速度增加10(5)x。拟议的启发式修复分析算法比提出的最佳算法快约28%,以牺牲5.8%的维修率损失。

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