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 $10^5\times$ 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.

中文翻译：

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具有冗余和内存中ECC的内存的高效修复分析算法探索

内存中纠错码（ECC）是一种有前途的技术，可以提高高密度存储器设计的良率和可靠性。然而，内存中ECC的使用给内存修复分析算法提出了一个新的问题，这是以前没有探讨过的。本文首先进行了定量评估，并证明具有冗余性和内存中ECC的简单内存算法在修复率或修复分析速度上均存在严重缺陷。因此，提出了一种利用预处理/过滤器算法，混合搜索树和深度优先搜索策略的最佳修复分析算法，以实现较低的计算复杂度和最佳修复率。此外，提出了一种使用贪婪策略的启发式维修分析算法，以有效地找到维修解决方案。$ 10 ^ 5 \ times $与简单的穷举搜索算法相比。所提出的启发式修复分析算法比所提出的最佳算法快大约28％，但损失了5.8％的修复率。