Chi-Feng Wu

Built-in redundancy analysis for memory yield improvement

With the advance of VLSI technology, the capacity and density of memories is rapidly growing. The yield improvement and testing issues have become the most critical challenges for memory manufacturing. Conventionally, redundancies are applied so that the faulty cells can be repairable. Redundancy analysis using external memory testers is becoming inefficient as the chip density continues to grow, especially for the system chip with large embedded memories. This paper presents three redundancy analysis algorithms which can be implemented on-chip. Among them, two are based on the local-bitmap idea: the local repair-most approach is efficient for a general spare architecture, and the local optimization approach has the best repair rate. The essential spare pivoting technique is proposed to reduce the control complexity. Furthermore, a simulator has been developed for evaluating the repair efficiency of different algorithms. It is also used for determining certain important parameters in redundancy design. The redundancy analysis circuit can easily be integrated with the built-in self-test circuit.

A programmable BIST core for embedded DRAM

The programmable BIST design presented here supports various test modes using a simple controller. With the March C algorithm, the BIST circuits overhead is under 1.3% for a 1-Mbit DRAM and under 0.3% for a 16-Mbit DRAM. The BIST design presented for embedded DRAM supports built-in self-diagnosis by feeding error information to the external tester. Moreover, using a specific test sequence, it can test for critical timing faults, reducing tester time for ac parametric test. The design supports wafer test, pre-burn-in test, burn-in, and final test. It is field-programmable; the user can program test algorithms using predetermined test elements (such as march elements, surround test elements, and refresh modes). The user can optimize the hardware for a specific embedded DRAM with a set of predetermined test elements. Our design is different from the microprogram-controlled BIST described by J. Dreibelbis et al. (1998) which has greater flexibility but higher overhead. Because our design begins at the register-transfer language level, test element insertion (for higher test coverage) and deletion (for lower hardware overhead are relatively easy.

RAMSES: a fast memory fault simulator

In this paper, we present a memory fault simulator called the Random Access Memory Simulator for Error Screening (RAMSES). Although it was designed based on some well-known memory fault models, the algorithm that we developed ensures that new fault models can be included easily by adding new fault descriptors instead of modifying the algorithm or program. With RAMSES, the time complexity of memory fault simulation is improved from O(N/sup 3/) to O(N/sup 2/), where N is the memory capacity in terns of bits. Our approach requires only a small amount of extra memory space. Simulation results by RAMSES show that running the proposed cocktail-March tests can significantly reduce the test time. With the help of RAMSES, an efficient test algorithm called March-CW was developed for word-oriented memories.

A built-in self-test and self-diagnosis scheme for embedded SRAM

Embedded memory test and diagnosis is becoming an important issue in system-on-chip (SOC) development. Direct access of the memory cores from the limited number of I/O pins is usually not feasible. Built-in self-diagnosis (BISD), which include built-in self-test (BIST), is rapidly becoming the most acceptable solution. We propose a BISD design and a fault diagnosis system for embedded SRAM. It supports manufacturing test as well as diagnosis for design verification and yield improvement. The proposed BISD circuit is on-line programmable for its March test algorithms. Test chips have been designed and implemented. Our experimental results show that the BISD hardware overhead is about 2.4% for a typical 128 Kb SRAM and only 0.65% for a 2 Mb SRAM.

Flash memory built-in self-test using March-like algorithms

Flash memories are a type of non-volatile memory based on floating-gate transistors. The use of commodity and embedded flash memories are growing rapidly as we enter the system-on-chip (SOC) era. Conventional tests for flash memories are usually ad hoc-the test procedure is developed for a specific design. We propose improved March-like algorithms (i.e., March FT) for both bit-oriented and word-oriented flash memory; to cover the disturbance faults derived from the IEEE 1005 Standard, as well as conventional faults. A novel flash memory fault simulator is used to analyze and generate the test algorithms. In addition, we present BIST designs for two industrial flash memories. The area overhead is only about 3% for a medium-sized flash memory.

Simulation-based test algorithm generation for random access memories

Although there are well known test algorithms that have been used by the industry for years for testing semiconductor random-access memories (RAMs), systematic evaluation of their effectiveness and efficiency has been a difficult job. In the past, it was mainly done manually by proving a certain algorithm can detect a certain type of fault. As memory technology keeps innovating, the growing complexity of the memories and number of fault types that need to be covered will require more effective and efficient test algorithms to be discovered in much shorter time. A systematic approach for developing and evaluating memory test algorithms is thus desired. We propose such an approach here: test algorithm generation by simulation (TAGS), which generates and optimizes test algorithms, given a test time budget. Experimental results show that the algorithms generated by TAGS are more efficient than the traditional test algorithms. Using TAGS, a series of test algorithms with a detailed list of faults covered by each algorithm can be generated, providing easy trade-off between test time and fault coverage.

Fault simulation and test algorithm generation for random access memories

The size and density of semiconductor memories is rapidly growing, making them increasingly harder to test. New fault models and test algorithms have been continuously proposed to cover defects and failures of modern memory chips and cores. However, software tool support for automating the memory test development procedure is still insufficient. For this purpose, we have developed a fault simulator (called RAMSES) and a test algorithm generator (called TAGS) for random-access memories (RAMs). In this paper, we present the algorithms and other details of RAMSES and TAGS and the experimental results of these tools on various memory architectures and configurations. We show that efficient test algorithms can be generated automatically for bit-oriented memories, word-oriented memories, and multiport memories, with 100% coverage of the given typical RAM faults.

A built-in self-test and self-diagnosis scheme for heterogeneous SRAM clusters

Testing and diagnosis are important issues in system-on-chip (SoC) development, as more and more embedded cores are being integrated into the chips. In this paper we propose a built-in self-test (BIST) and self-diagnosis (BISD) scheme for embedded SRAMs, suitable for SoC applications. It supports manufacturing test as well as diagnosis for design verification and yield improvement. With low hardware cost, our memory BISD approach can handle various types of SRAM, including pipelined, multi-port, and multi-clock architectures. In addition, a test scheduling methodology and a BISD compiler are also implemented, which reduce the testing time as well as test development time.

Simulation-based test algorithm generation and port scheduling for multi-port memories

The paper presents a simulation-based test algorithm generation and test scheduling methodology for multi-port memories. The purpose is to minimize the testing time while keeping the test algorithm in a simple and regular format for easy test generation, fault diagnosis, and built-in self-test (BIST) circuit implementation. Conventional functional fault models are used to generate tests covering most defects. In addition, multi-port specific defects are covered using structural fault models. Port-scheduling is introduced to take advantage of the inherent parallelism among different ports. Experimental results for commonly used multi-port memories, including dual-port, four-port, and

A Built-in Self-Test Scheme with Diagnostics Support for Embedded SRAM

n