Efficient Built In Self Repair Strategy for Embedded SRAM with selecteble redundancy

Built-in self -test (BIST) refers to those testing techniques where additional hardware is added to a design so that testing is accomplished without the aid of external hardware. Usually, a pseudo-random generator is used to apply test vectors to the circuit under test and a data compactor is used to produce a signature. To increase the reliability and yield of embedded memories, many redundancy mechanisms have been proposed. All the redundancy mechanisms bring penalty of area and complexity to embedded memories design. Considered that compiler is used to configure SRAM for different needs, the BISR had better bring no change to other modules in SRAM. To solve the problem, a new redundancy scheme is proposed in this paper. Some normal words in embedded memories can be selected as redundancy instead of adding spare words, spare rows, spare columns or spare blocks. Built-In Self-Repair (BISR) with Redundancy is an effective yield-enhancement strategy for embedded memories. This paper proposes an efficient BISR strategy which consists of a Built-In Self-Test (BIST) module, a Built-In Address-Analysis (BIAA) module and a Multiplexer (MUX) module. The BISR is designed flexible that it can provide four operation modes to SRAM users. Each fault address can be saved only once is the feature of the proposed BISR strategy. In BIAA module, fault addresses and redundant ones form a one- to- one mapping to achieve a high repair speed. Besides, instead of adding spare words, rows, columns or blocks in the SRAMs, users can select normal words as redundancy

Memory built-in self-repair and correction for improving yield: a review

Nanometer memories are highly prone to defects due to dense structure, necessitating memory built-in self-repair as a must-have feature to improve yield. Today’s system-on-chips contain memories occupying an area as high as 90% of the chip area. Shrinking technology uses stricter design rules for memories, making them more prone to manufacturing defects. Further, using 3D-stacked memories makes the system vulnerable to newer defects such as those coming from through-silicon-vias (TSV) and micro bumps. The increased memory size is also resulting in an increase in soft errors during system operation. Multiple memory repair techniques based on redundancy and correction codes have been presented to recover from such defects and prevent system failures. This paper reviews recently published memory repair methodologies, including various built-in self-repair (BISR) architectures, repair analysis algorithms, in-system repair, and soft repair handling using error correcting codes (ECC). It provides a classification of these techniques based on method and usage. Finally, it reviews evaluation methods used to determine the effectiveness of the repair algorithms. The paper aims to present a survey of these methodologies and prepare a platform for developing repair methods for upcoming-generation memories

A machine learning-based approach to optimize repair and increase yield of embedded flash memories in automotive systems-on-chip

Nowadays, Embedded Flash Memory cores occupy a significant portion of Automotive Systems-on-Chip area, therefore strongly contributing to the final yield of the devices. Redundancy strategies play a key role in this context; in case of memory failures, a set of spare word- and bit-lines are allocated by a replacement algorithm that complements the memory testing procedure. In this work, we show that replacement algorithms, which are heavily constrained in terms of execution time, may be slightly inaccurate and lead to classify a repairable memory core as unrepairable. We denote this situation as Flash memory false fail. The proposed approach aims at identifying false fails by using a Machine Learning approach that exploits a feature extraction strategy based on shape recognition. Experimental results carried out on the manufacturing data show a high capability of predicting false fails

Lessons learned in creating spacecraft computer systems: Implications for using Ada (R) for the space station

Twenty-five years of spacecraft onboard computer development have resulted in a better understanding of the requirements for effective, efficient, and fault tolerant flight computer systems. Lessons from eight flight programs (Gemini, Apollo, Skylab, Shuttle, Mariner, Voyager, and Galileo) and three reserach programs (digital fly-by-wire, STAR, and the Unified Data System) are useful in projecting the computer hardware configuration of the Space Station and the ways in which the Ada programming language will enhance the development of the necessary software. The evolution of hardware technology, fault protection methods, and software architectures used in space flight in order to provide insight into the pending development of such items for the Space Station are reviewed

Fault-tolerant computer study

A set of building block circuits is described which can be used with commercially available microprocessors and memories to implement fault tolerant distributed computer systems. Each building block circuit is intended for VLSI implementation as a single chip. Several building blocks and associated processor and memory chips form a self checking computer module with self contained input output and interfaces to redundant communications buses. Fault tolerance is achieved by connecting self checking computer modules into a redundant network in which backup buses and computer modules are provided to circumvent failures. The requirements and design methodology which led to the definition of the building block circuits are discussed

Defending cache memory against cold-boot attacks boosted by power or EM radiation analysis

Some algorithms running with compromised data select cache memory as a type of secure memory where data is confined and not transferred to main memory. However, cold-boot attacks that target cache memories exploit the data remanence. Thus, a sudden power shutdown may not delete data entirely, giving the opportunity to steal data. The biggest challenge for any technique aiming to secure the cache memory is performance penalty. Techniques based on data scrambling have demonstrated that security can be improved with a limited reduction in performance. However, they still cannot resist side-channel attacks like power or electromagnetic analysis. This paper presents a review of known attacks on memories and countermeasures proposed so far and an improved scrambling technique named random masking interleaved scrambling technique (RM-ISTe). This method is designed to protect the cache memory against cold-boot attacks, even if these are boosted by side-channel techniques like power or electromagnetic analysis.Postprint (author's final draft