Minimum fault coverage in memory arrays: a fast algorithm and probabilistic analysis

Dept. of Inf. Syst. & Comput. Sci., Nat. Univ. of Singapore
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems (Impact Factor: 1). 07/1996; 15(6):681 - 690. DOI: 10.1109/43.503937
Source: IEEE Xplore


The problem of reconfiguring memory arrays using spare rows and
spare columns is known to be NP-complete and has received a great deal
of attention in recent years. For reason of cost effectiveness, it is
desirable in practice to find minimum reconfiguration solutions. While
numerous algorithms have been proposed to find minimum reconfiguration
solutions, they all run in worst case exponential time complexities. On
the other hand, existing heuristic algorithms with fast polynomial
running time cannot guarantee minimum solutions. This paper presents a
provably good heuristic algorithm for finding minimum reconfiguration
solution. Using random bipartite graphs, we prove that the
reconfiguration problem is almost always optimally solvable with our new
algorithm in polynomial time for all practical purposes. We also show
that our algorithm can be used to estimate the number of spare rows and
columns that are required to achieve a given percentage of yield for
RRAM's with known defect probabilities

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    • "Approaches for improving the throughput have been proposed [6]. Many other heuristic algorithms are also proposed to reduce the time of searching for a repair solution [2] [3] [4] [7] [8] [9] [10] [11]. Though these heuristic algorithms are very efficient, they have a common drawback: they cannot guarantee a solution to be found even if one exists. "
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    ABSTRACT: Redundant rows and columns have been used for years to improve the yield of DRAM fabrication. However, finding a memory repair solution has been proved to be an NP-complete problem. This paper presents an efficient algorithm, which is able to find a repair solution for shared spare memory arrays if a solution exists. The remarkable performance of the algorithm can be demonstrated by experimental results.
    Preview · Conference Paper · Nov 2004
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    ABSTRACT: This paper introduces a novel procedure of identifying better representatives of faulty cells in a memory map to help judge unrepairability and provide economic repair recommendation. These representative faulty cells, called leading elements (LE), are classified into four primary types based on their characteristics. Three specific pairs of initially identified LE are extracted for further operations, which are replacing certain LE with other better representatives and assigning the cross point faults between two certain LE as new LE. All steps of the procedure are analyzed in sequence with verifi- cation, clearly indicating that the identified LE represent both the more exact thresholds for judging unrepairability and usually the most economic repair solutions. Experi- ments on many example maps show that the procedure can be fast in searching 7% more LE and be applicable to accumulate data for redundancy planning afterwards.
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    ABSTRACT: This paper consider the problem of reconfiguring two dimensional very large scale integration (VLSI/WSI) arrays via the degradation approach. In this approach, all elements are treated uniformly and no elements are dedicated as spares. The goal is to derive a fault-free subarray T from the defective host array such that the dimensions of T are larger than some specified minimum. This problem has been shown to be NP-complete under various switching and routing constraints. However, we show that a special case of the reconfiguration problem with row bypass and column rerouting capabilities is optimally solvable in linear time. Using this result, a new fast and efficient reconfiguration algorithm is proposed. Empirical study shows that the new algorithm indeed produces good results in terms of the percentages of harvest and degradation of VLSI/WSI arrays
    No preview · Article · Nov 1997 · IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
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