Built-in Redundancy Analysis Algorithm Research Articles

An Efficient BIRA Utilizing Characteristics of Spare Pivot Faults

The current growth of micro-semiconductor technologies requires that an effective solution be found to address the yield and reliability issues associated with embedded memories. A common solution is built-in redundancy analysis (BIRA), which is utilized to guarantee reasonable memory yields. The most common form of BIRA is a module that stores and analyzes fault addresses with a 2-D spare architecture. When the performance of BIRA is evaluated, numerous different parameters are considered, such as repair rate, area overhead, and analysis speed. Because there is a tradeoff between these criteria, many BIRA approaches have been studied so that an ideal BIRA can be found. A novel BIRA approach that focuses on a 100% repair rate and a minimal area overhead is proposed in this paper. In the fault collection phase, the proposed BIRA stores only the essential part of fault addresses in content addressable memories (CAMs), with the rest of the fault addresses being stored in spare memories. After the fault collection phase, a redundancy analysis procedure is performed with the minimum amount of fault information that is stored in the proposed CAM structure. By doing so, the proposed BIRA algorithm can repair all repairable faulty memories while maintaining a minimal area overhead. Our experimental results confirm that the proposed approach exhibits outstanding performance for area overhead, especially when compared to other BIRA approaches that have 100% repair rates.

A 3 Dimensional Built-In Self-Repair Scheme for Yield Improvement of 3 Dimensional Memories

A 3-dimensional Built-In Self-Repair (3D BISR) scheme is proposed for 3-dimensional (3D) memories. The proposed 3D BISR scheme consists of two phases: a parallel test-repair phase, and a serial test-repair phase. After all memory dice are simultaneously tested, only the faulty memory dice are serially tested and repaired using one Built-In Redundancy Analysis (BIRA) module. Thus, it is a faster test-repair with low area overhead. The proposed BIRA algorithm with a post-share redundancy scheme performs exhaustive searches for all combinations of spare rows and columns. Experimental results show that the proposed 3D BISR is up to two times faster than the 3D serial test-serial repair BISR when seven 2048 $\times$ 2048 bit memory dice are stacked. The proposed 3D BISR requires 44.55% of the area in comparison to a 3D parallel test-parallel repair BISR for four stacked memory dice (one 128 K RAM, two 256 K RAMs, and 512 K RAM). The yield of 3D memories is the highest due to the exhaustive search BIRA algorithm with the post-share redundancy scheme as shown in various experimental results.

A Low-Cost Built-In Redundancy-Analysis Scheme for Word-Oriented RAMs With 2-D Redundancy

Built-in self-repair (BISR) techniques are widely used for repairing embedded random access memories (RAMs). One key component of a BISR module is the built-in redundancy-analysis (BIRA) design. This paper presents an effective BIRA scheme which executes the 2-D redundancy allocation based on a 1-D local bitmap. Two BIRA algorithms for supporting two different redundancy organizations are also proposed. Simulation results show that the proposed BIRA scheme can provide high repair rate (i.e., the ratio of the number of repaired memories to the number of defective memories) for the RAMs with different fault distributions. Experimental results show that the hardware overhead of the BIRA design is only about 2.9% for an 8192 × 64-bit RAM with two spare rows and two spare columns. Also, the ratio of the BIRA analysis time to the test time is only about 0.02% if the March-CW test is performed. Furthermore, a simulation flow is proposed to determine the size of the 1-D local bitmap such that the BIRA algorithm can provide the best repair rate using the smallest-size 1-D local bitmap.

A Built-In Redundancy Analysis with a Minimized Binary Search Tree

With the growth of memory capacity and density, memory testing and repair with the goal of yield improvement have become more important. Therefore, the development of high efficiency redundancy analysis algorithms is essential to improve yield rate. In this letter, we propose an improved built-in redundancy analysis (BIRA) algorithm with a minimized binary search tree made by simple calculations. The tree is constructed until finding a solution from the most probable branch. This greatly reduces the search spaces for a solution. The proposed BIRA algorithm results in 100% repair efficiency and fast redundancy analysis.

High Repair Efficiency BIRA Algorithm with a Line Fault Scheme

With the rapid increase occurring in both the capacity and density of memory products, test and repair issues have become highly challenging. Memory repair is an effective and essential methodology for improving memory yield. An SoC utilizes builtin redundancy analysis (BIRA) with built-in self-test for improving memory yield and reliability. This letter proposes a new heuristic algorithm and new hardware architecture for the BIRA scheme. Experimental results indicate that the proposed algorithm shows near-optimal repair efficiency in combination with low area and time overheads.

EOF: Efficient Built-In Redundancy Analysis Methodology With Optimal Repair Rate

Faulty cell repair with redundancy can improve memory yield. In particular, built-in redundancy analysis (BIRA) is widely used to enhance the yield of embedded memories. We propose an efficient BIRA algorithm to achieve the optimal repair rate with a very short analysis time and low hardware cost. The proposed algorithm can significantly reduce the number of backtracks in the exhaustive search algorithm: it uses early termination based on the number of orthogonal faulty cells and fault classification in fault collection. Experimental results show that the proposed BIRA methodology can achieve optimal repair rate with low hardware overhead and short analysis time, as compared to previous BIRA methods.