Automating defects simulation and fault modeling for SRAMs

The continues improvement in manufacturing process density for very deep sub micron technologies constantly leads to new classes of defects in memory devices. Exploring the effect of fabrication defects in future technologies, and identifying new classes of realistic functional fault models with their corresponding test sequences, is a time consuming task up to now mainly performed by hand. This paper proposes a new approach to automate this procedure. The proposed method exploits the capabilities of evolutionary algorithms to automatically identify faulty behaviors into defective memories and to define the corresponding fault models and relevant test sequences. Target defects are modeled at the electrical level in order to optimize the results to the specific technology and memory architecture

A Low-Cost FPGA-Based Test and Diagnosis Architecture for SRAMs

The continues improvement of manufacturing technologies allows the realization of integrated circuits containing an ever increasing number of transistors. A major part of these devices is devoted to realize SRAM blocks. Test and diagnosis of SRAM circuits are therefore an important challenge for improving quality of next generation integrated circuits. This paper proposes a flexible platform for testing and diagnosis of SRAM circuits. The architecture is based on the use of a low cost FPGA based board allowing high diagnosability while keeping costs at a very low leve

Genetic Defect Based March Test Generation for SRAM

The continuos shrinking of semiconductor's nodes makes semiconductor memories increasingly prone to electrical defects tightly related to the internal structure of the memory. Exploring the effect of fabrication defects in future technologies, and identifying new classes of functional fault models with their corresponding test sequences, is a time consuming task up to now mainly performed by hand. This paper pro- poses a new approach to automate this procedure exploiting a dedicated genetic algorithm

Comparing different solutions for testing resistive defects in low-power SRAMs

Low-power SRAM architectures are especially sensitive to many types of defects that may occur during manufacturing. Among these, resistive defects can appear. This paper analyzes some types of such defects that may impair the device functionalities in subtle ways, depending on the defect characteristics, and that may not be directly or easily detectable by traditional test methods, such as March algorithms. We analyze different methods to test such defects and discuss them in terms of complexity and test time

An Experimental Evaluation of Resistive Defects and Different Testing Solutions in Low-Power Back-Biased SRAM Cells

This paper compares different types of resistive defects that may occur inside low-power SRAM cells, focusing on their impact on device operation. Notwithstanding the continuous evolution of SRAM device integration, manufacturing processes continue to be very sensitive to production faults, giving rise to defects that can be modeled as resistances, especially for devices designed to work in low-power modes. This work analyzes this type of resistive defect that may impair the device functionalities in subtle ways, depending on the defect characteristics and values that may not be directly or easily detectable by traditional test methods. We analyze each defect in terms of the possible effects inside the SRAM cell, its impact on power consumption, and provide guidelines for selecting the best test methods

Fault Tolerant Electronic System Design

Due to technology scaling, which means reduced transistor size, higher density, lower voltage and more aggressive clock frequency, VLSI devices may become more sensitive against soft errors. Especially for those devices used in safety- and mission-critical applications, dependability and reliability are becoming increasingly important constraints during the development of system on/around them. Other phenomena (e.g., aging and wear-out effects) also have negative impacts on reliability of modern circuits. Recent researches show that even at sea level, radiation particles can still induce soft errors in electronic systems. On one hand, processor-based system are commonly used in a wide variety of applications, including safety-critical and high availability missions, e.g., in the automotive, biomedical and aerospace domains. In these fields, an error may produce catastrophic consequences. Thus, dependability is a primary target that must be achieved taking into account tight constraints in terms of cost, performance, power and time to market. With standards and regulations (e.g., ISO-26262, DO-254, IEC-61508) clearly specify the targets to be achieved and the methods to prove their achievement, techniques working at system level are particularly attracting. On the other hand, Field Programmable Gate Array (FPGA) devices are becoming more and more attractive, also in safety- and mission-critical applications due to the high performance, low power consumption and the flexibility for reconfiguration they provide. Two types of FPGAs are commonly used, based on their configuration memory cell technology, i.e., SRAM-based and Flash-based FPGA. For SRAM-based FPGAs, the SRAM cells of the configuration memory highly susceptible to radiation induced effects which can leads to system failure; and for Flash-based FPGAs, even though their non-volatile configuration memory cells are almost immune to Single Event Upsets induced by energetic particles, the floating gate switches and the logic cells in the configuration tiles can still suffer from Single Event Effects when hit by an highly charged particle. So analysis and mitigation techniques for Single Event Effects on FPGAs are becoming increasingly important in the design flow especially when reliability is one of the main requirements

SEU sensitivity and modeling using picosecond pulsed laser stimulation of a D Flip-Flop in 40 nm CMOS technology

International audience—This paper presents the design of a CMOS 40 nm D Flip-Flop cell and reports the laser fault sensitivity mapping both with experiments and simulation results. Theses studies are driven by the need to propose a simulation methodology based on laser/silicon interactions with a complex integrated circuit. In the security field, it is therefore mandatory to understand the behavior of sensitive devices like D Flip-Flops to laser stimulation. In previous works, Roscian et al., Sarafianos et al., Lacruche et al. or Courbon et al. studied the relations between the layout of cells, its different laser-sensitive areas and their associated fault model using laser pulse duration in the nanosecond range. In this paper, we report similar experiments carried out using a shorter laser pulse duration (30 ps instead of 50 ns). We also propose an upgrade of the simulation model they used to take into account laser pulse durations in the picosecond range on a logic gate composed of a large number of transistors for a recent CMOS technology (40 nm)

Using Fine Grain Approaches for highly reliable Design of FPGA-based Systems in Space

Nowadays using SRAM based FPGAs in space missions is increasingly considered due to their flexibility and reprogrammability. A challenge is the devices sensitivity to radiation effects that increased with modern architectures due to smaller CMOS structures. This work proposes fault tolerance methodologies, that are based on a fine grain view to modern reconfigurable architectures. The focus is on SEU mitigation challenges in SRAM based FPGAs which can result in crucial situations

UA2TPG: An untestability analyzer and test pattern generator for SEUs in the configuration memory of SRAM-based FPGAs

This paper presents UA2TPG, a static analysis tool for the untestability proof and automatic test pattern generation for SEUs in the configuration memory of SRAM-based FPGA systems. The tool is based on the model-checking verification technique. An accurate fault model for both logic components and routing structures is adopted. Experimental results show that many circuits have a significant number of untestable faults, and their detection enables more efficient test pattern generation and on-line testing. The tool is mainly intended to support on-line testing of critical components in FPGA fault-tolerant systems