Infrastructures and Algorithms for Testable and Dependable Systems-on-a-Chip

Every new node of semiconductor technologies provides further miniaturization and higher performances, increasing the number of advanced functions that electronic products can offer. Silicon area is now so cheap that industries can integrate in a single chip usually referred to as System-on-Chip (SoC), all the components and functions that historically were placed on a hardware board. Although adding such advanced functionality can benefit users, the manufacturing process is becoming finer and denser, making chips more susceptible to defects. Today’s very deep-submicron semiconductor technologies (0.13 micron and below) have reached susceptibility levels that put conventional semiconductor manufacturing at an impasse. Being able to rapidly develop, manufacture, test, diagnose and verify such complex new chips and products is crucial for the continued success of our economy at-large. This trend is expected to continue at least for the next ten years making possible the design and production of 100 million transistor chips. To speed up the research, the National Technology Roadmap for Semiconductors identified in 1997 a number of major hurdles to be overcome. Some of these hurdles are related to test and dependability. Test is one of the most critical tasks in the semiconductor production process where Integrated Circuits (ICs) are tested several times starting from the wafer probing to the end of production test. Test is not only necessary to assure fault free devices but it also plays a key role in analyzing defects in the manufacturing process. This last point has high relevance since increasing time-to-market pressure on semiconductor fabrication often forces foundries to start volume production on a given semiconductor technology node before reaching the defect densities, and hence yield levels, traditionally obtained at that stage. The feedback derived from test is the only way to analyze and isolate many of the defects in today’s processes and to increase process’s yield. With the increasing need of high quality electronic products, at each new physical assembly level, such as board and system assembly, test is used for debugging, diagnosing and repairing the sub-assemblies in their new environment. Similarly, the increasing reliability, availability and serviceability requirements, lead the users of high-end products performing periodic tests in the field throughout the full life cycle. To allow advancements in each one of the above scaling trends, fundamental changes are expected to emerge in different Integrated Circuits (ICs) realization disciplines such as IC design, packaging and silicon process. These changes have a direct impact on test methods, tools and equipment. Conventional test equipment and methodologies will be inadequate to assure high quality levels. On chip specialized block dedicated to test, usually referred to as Infrastructure IP (Intellectual Property), need to be developed and included in the new complex designs to assure that new chips will be adequately tested, diagnosed, measured, debugged and even sometimes repaired. In this thesis, some of the scaling trends in designing new complex SoCs will be analyzed one at a time, observing their implications on test and identifying the key hurdles/challenges to be addressed. The goal of the remaining of the thesis is the presentation of possible solutions. It is not sufficient to address just one of the challenges; all must be met at the same time to fulfill the market requirements

Yield estimation of a memristive sensor array

This paper proposes a method to calculate the yield of a memristor based sensor array considered as the probability that the chip provides acceptable sensing results when the array is affected by manufacturing defects. The modeling is based on a Markov Chain approach, in which each state represents an operating chip configuration and the state transitions take into account manufacturing defects. The proposed method is applicable to evaluate the yield with different fault models to achieve the comparative yield obtained by several redundancy allocations

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

Innovative Techniques for Testing and Diagnosing SoCs

We rely upon the continued functioning of many electronic devices for our everyday welfare, usually embedding integrated circuits that are becoming even cheaper and smaller with improved features. Nowadays, microelectronics can integrate a working computer with CPU, memories, and even GPUs on a single die, namely System-On-Chip (SoC). SoCs are also employed on automotive safety-critical applications, but need to be tested thoroughly to comply with reliability standards, in particular the ISO26262 functional safety for road vehicles. The goal of this PhD. thesis is to improve SoC reliability by proposing innovative techniques for testing and diagnosing its internal modules: CPUs, memories, peripherals, and GPUs. The proposed approaches in the sequence appearing in this thesis are described as follows: 1. Embedded Memory Diagnosis: Memories are dense and complex circuits which are susceptible to design and manufacturing errors. Hence, it is important to understand the fault occurrence in the memory array. In practice, the logical and physical array representation differs due to an optimized design which adds enhancements to the device, namely scrambling. This part proposes an accurate memory diagnosis by showing the efforts of a software tool able to analyze test results, unscramble the memory array, map failing syndromes to cell locations, elaborate cumulative analysis, and elaborate a final fault model hypothesis. Several SRAM memory failing syndromes were analyzed as case studies gathered on an industrial automotive 32-bit SoC developed by STMicroelectronics. The tool displayed defects virtually, and results were confirmed by real photos taken from a microscope. 2. Functional Test Pattern Generation: The key for a successful test is the pattern applied to the device. They can be structural or functional; the former usually benefits from embedded test modules targeting manufacturing errors and is only effective before shipping the component to the client. The latter, on the other hand, can be applied during mission minimally impacting on performance but is penalized due to high generation time. However, functional test patterns may benefit for having different goals in functional mission mode. Part III of this PhD thesis proposes three different functional test pattern generation methods for CPU cores embedded in SoCs, targeting different test purposes, described as follows: a. Functional Stress Patterns: Are suitable for optimizing functional stress during I Operational-life Tests and Burn-in Screening for an optimal device reliability characterization b. Functional Power Hungry Patterns: Are suitable for determining functional peak power for strictly limiting the power of structural patterns during manufacturing tests, thus reducing premature device over-kill while delivering high test coverage c. Software-Based Self-Test Patterns: Combines the potentiality of structural patterns with functional ones, allowing its execution periodically during mission. In addition, an external hardware communicating with a devised SBST was proposed. It helps increasing in 3% the fault coverage by testing critical Hardly Functionally Testable Faults not covered by conventional SBST patterns. An automatic functional test pattern generation exploiting an evolutionary algorithm maximizing metrics related to stress, power, and fault coverage was employed in the above-mentioned approaches to quickly generate the desired patterns. The approaches were evaluated on two industrial cases developed by STMicroelectronics; 8051-based and a 32-bit Power Architecture SoCs. Results show that generation time was reduced upto 75% in comparison to older methodologies while increasing significantly the desired metrics. 3. Fault Injection in GPGPU: Fault injection mechanisms in semiconductor devices are suitable for generating structural patterns, testing and activating mitigation techniques, and validating robust hardware and software applications. GPGPUs are known for fast parallel computation used in high performance computing and advanced driver assistance where reliability is the key point. Moreover, GPGPU manufacturers do not provide design description code due to content secrecy. Therefore, commercial fault injectors using the GPGPU model is unfeasible, making radiation tests the only resource available, but are costly. In the last part of this thesis, we propose a software implemented fault injector able to inject bit-flip in memory elements of a real GPGPU. It exploits a software debugger tool and combines the C-CUDA grammar to wisely determine fault spots and apply bit-flip operations in program variables. The goal is to validate robust parallel algorithms by studying fault propagation or activating redundancy mechanisms they possibly embed. The effectiveness of the tool was evaluated on two robust applications: redundant parallel matrix multiplication and floating point Fast Fourier Transform

Selected topics in robotics for space exploration

Papers and abstracts included represent both formal presentations and experimental demonstrations at the Workshop on Selected Topics in Robotics for Space Exploration which took place at NASA Langley Research Center, 17-18 March 1993. The workshop was cosponsored by the Guidance, Navigation, and Control Technical Committee of the NASA Langley Research Center and the Center for Intelligent Robotic Systems for Space Exploration (CIRSSE) at RPI, Troy, NY. Participation was from industry, government, and other universities with close ties to either Langley Research Center or to CIRSSE. The presentations were very broad in scope with attention given to space assembly, space exploration, flexible structure control, and telerobotics

Test and Diagnosis of Integrated Circuits

The ever-increasing growth of the semiconductor market results in an increasing complexity of digital circuits. Smaller, faster, cheaper and low-power consumption are the main challenges in semiconductor industry. The reduction of transistor size and the latest packaging technology (i.e., System-On-a-Chip, System-In-Package, Trough Silicon Via 3D Integrated Circuits) allows the semiconductor industry to satisfy the latest challenges. Although producing such advanced circuits can benefit users, the manufacturing process is becoming finer and denser, making chips more prone to defects.The work presented in the HDR manuscript addresses the challenges of test and diagnosis of integrated circuits. It covers:- Power aware test;- Test of Low Power Devices;- Fault Diagnosis of digital circuits

A Study of Nanometer Semiconductor Scaling Effects on Microelectronics Reliability

The desire to assess the reliability of emerging scaled microelectronics technologies through faster reliability trials and more accurate acceleration models is the precursor for further research and experimentation in this relevant field. The effect of semiconductor scaling on microelectronics product reliability is an important aspect to the high reliability application user. From the perspective of a customer or user, who in many cases must deal with very limited, if any, manufacturer's reliability data to assess the product for a highly-reliable application, product-level testing is critical in the characterization and reliability assessment of advanced nanometer semiconductor scaling effects on microelectronics reliability. This dissertation provides a methodology on how to accomplish this and provides techniques for deriving the expected product-level reliability on commercial memory products. Competing mechanism theory and the multiple failure mechanism model are applied to two separate experiments; scaled SRAM and SDRAM products. Accelerated stress testing at multiple conditions is applied at the product level of several scaled memory products to assess the performance degradation and product reliability. Acceleration models are derived for each case. For several scaled SDRAM products, retention time degradation is studied and two distinct soft error populations are observed with each technology generation: early breakdown, characterized by randomly distributed weak bits with Weibull slope Beta=1, and a main population breakdown with an increasing failure rate. Retention time soft error rates are calculated and a multiple failure mechanism acceleration model with parameters is derived for each technology. Defect densities are calculated and reflect a decreasing trend in the percentage of random defective bits for each successive product generation. A normalized soft error failure rate of the memory data retention time in FIT/Gb and FIT/cm2 for several scaled SDRAM generations is presented revealing a power relationship. General models describing the soft error rates across scaled product generations are presented. The analysis methodology may be applied to other scaled microelectronic products and key parameters

NASA Tech Briefs, December 1988

This month's technical section includes forecasts for 1989 and beyond by NASA experts in the following fields: Integrated Circuits; Communications; Computational Fluid Dynamics; Ceramics; Image Processing; Sensors; Dynamic Power; Superconductivity; Artificial Intelligence; and Flow Cytometry. The quotes provide a brief overview of emerging trends, and describe inventions and innovations being developed by NASA, other government agencies, and private industry that could make a significant impact in coming years. A second bonus feature in this month's issue is the expanded subject index that begins on page 98. The index contains cross-referenced listings for all technical briefs appearing in NASA Tech Briefs during 1988