9 research outputs found

    Reducing Library Characterization Time for Cell-aware Test while Maintaining Test Quality

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    Cell-aware test (CAT) explicitly targets faults caused by defects inside library cells to improve test quality, compared with conventional automatic test pattern generation (ATPG) approaches, which target faults only at the boundaries of library cells. The CAT methodology consists of two stages. Stage 1, based on dedicated analog simulation, library characterization per cell identifies which cell-level test pattern detects which cell-internal defect; this detection information is encoded in a defect detection matrix (DDM). In Stage 2, with the DDMs as inputs, cell-aware ATPG generates chip-level test patterns per circuit design that is build up of interconnected instances of library cells. This paper focuses on Stage 1, library characterization, as both test quality and cost are determined by the set of cell-internal defects identified and simulated in the CAT tool flow. With the aim to achieve the best test quality, we first propose an approach to identify a comprehensive set, referred to as full set, of potential open- and short-defect locations based on cell layout. However, the full set of defects can be large even for a single cell, making the time cost of the defect simulation in Stage 1 unaffordable. Subsequently, to reduce the simulation time, we collapse the full set to a compact set of defects which serves as input of the defect simulation. The full set is stored for the diagnosis and failure analysis. With inspecting the simulation results, we propose a method to verify the test quality based on the compact set of defects and, if necessary, to compensate the test quality to the same level as that based on the full set of defects. For 351 combinational library cells in Cadence’s GPDK045 45nm library, we simulate only 5.4% defects from the full set to achieve the same test quality based on the full set of defects. In total, the simulation time, via linear extrapolation per cell, would be reduced by 96.4% compared with the time based on the full set of defects

    Optimization of Cell-Aware Test

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    Optimization of Cell-Aware Test

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    Test and Diagnosis of Integrated Circuits

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    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

    AI/ML Algorithms and Applications in VLSI Design and Technology

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    An evident challenge ahead for the integrated circuit (IC) industry in the nanometer regime is the investigation and development of methods that can reduce the design complexity ensuing from growing process variations and curtail the turnaround time of chip manufacturing. Conventional methodologies employed for such tasks are largely manual; thus, time-consuming and resource-intensive. In contrast, the unique learning strategies of artificial intelligence (AI) provide numerous exciting automated approaches for handling complex and data-intensive tasks in very-large-scale integration (VLSI) design and testing. Employing AI and machine learning (ML) algorithms in VLSI design and manufacturing reduces the time and effort for understanding and processing the data within and across different abstraction levels via automated learning algorithms. It, in turn, improves the IC yield and reduces the manufacturing turnaround time. This paper thoroughly reviews the AI/ML automated approaches introduced in the past towards VLSI design and manufacturing. Moreover, we discuss the scope of AI/ML applications in the future at various abstraction levels to revolutionize the field of VLSI design, aiming for high-speed, highly intelligent, and efficient implementations

    Improvement of hardware reliability with aging monitors

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    At-Speed Path Delay Test

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    This research describes an approach to test metastability of flip-flops with help of multiple at-speed capture cycles during delay test. K longest paths per flip-flop test patterns are generated, such that a long path on one clock cycle feeds a long path on the next clock cycle, and so on. Traditional structural delay tests do not test whether time borrowing or stealing is working correctly, since only a single at-speed cycle is tested. To detect path delay faults for the multi-cycle paths, it is necessary to start a path at a register and end at a register while passing through another register, testing the longest paths between each pair of registers. This requires three or more at-speed cycles, rather than the two of traditional Launch on Capture test. This produces power supply noise closer to functional mode, and permits the testing of flip-flop metastability and time-borrowing latches, that cannot be tested by any other structural test technique. The path generation algorithm uses the circuit structure, and then the paths are sequentially justified using Boolean Satisfiability algorithms. The algorithm has been implemented in C++ on an Intel Core i7 machine. Experiments have been performed on various ISCAS benchmark circuits in both robust and non-robust path generation technique to evaluate our approach

    Dependable Embedded Systems

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    This Open Access book introduces readers to many new techniques for enhancing and optimizing reliability in embedded systems, which have emerged particularly within the last five years. This book introduces the most prominent reliability concerns from today’s points of view and roughly recapitulates the progress in the community so far. Unlike other books that focus on a single abstraction level such circuit level or system level alone, the focus of this book is to deal with the different reliability challenges across different levels starting from the physical level all the way to the system level (cross-layer approaches). The book aims at demonstrating how new hardware/software co-design solution can be proposed to ef-fectively mitigate reliability degradation such as transistor aging, processor variation, temperature effects, soft errors, etc. Provides readers with latest insights into novel, cross-layer methods and models with respect to dependability of embedded systems; Describes cross-layer approaches that can leverage reliability through techniques that are pro-actively designed with respect to techniques at other layers; Explains run-time adaptation and concepts/means of self-organization, in order to achieve error resiliency in complex, future many core systems

    Cross-layer fault tolerance in networks-on-chip

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    The design of Networks-on-Chip follows the Open Systems Interconnection (OSI) reference model. The OSI model defines strictly separated network abstraction layers and specifies their functionality. Each layer has layer-specific information about the network that can be exclusively accessed by the methods of the layer. Adhering to the strict layer boundaries, however, leads to methods of the individual layers working in isolation from each other. This lack of interaction between methods is disadvantageous for fault diagnosis and fault tolerance in Networks-on-Chip as it results in solutions that have a high effort in terms of the time and implementation costs required to deal with faults. For Networks-on-Chip cross-layer design is considered as a promising method to remedy these shortcomings. It removes the strict layer boundaries by the exchange of information between layers. This interaction enables methods of different layers to cooperate, and thus, deal with faults more efficiently. Furthermore, providing lower layer information to the software allows hardware methods to be implemented as software tasks resulting in a reduction of the hardware complexity. The goal of this dissertation is the investigation of cross-layer design for fault diagnosis and fault tolerance in Networks-on-Chip. For fault diagnosis a scheme is proposed that allows the interaction of protocol-based diagnosis of the transport layer with functional diagnosis of the network layer and structural diagnosis of the physical layer by exchanging diagnostic information. The techniques use this information for optimizing their own diagnosis process. For protocol-based diagnosis on the transport layer, a diagnosis protocol is proposed that is able to locate faulty links, switches, and crossbar connections. For this purpose, the technique utilizes available information of lower layers. As proof of concept for the proposed interaction scheme, the diagnosis protocol is combined with a functional and a structural diagnosis approach and the performance and diagnosis quality of the resulting combinations is investigated. The results show that the combinations of the diagnosis protocol with one of the lower layer techniques have a considerably reduced fault localization latency compared to the functional and the structural standalone techniques. This reduction, however, comes at the expense of a reduced diagnosis quality. In terms of fault tolerance, the focus of this dissertation is on the design and implementation of cross-layer approaches utilizing software methods to provide fault tolerance for network layer routings. Two approaches for different routings are presented. The requirements to provide information of lower layers to the software using the available Network-on-Chip resources and interfaces for data communication are discussed. The concepts of two mechanisms of the data link layer are presented for converting status information into communicable units and for preventing communication resources from being blocked. In the first approach, software-based packet rerouting is proposed. By incorporating information from different layers, this approach provides fault tolerance for deterministic network layer routings. As specialization of software-based rerouting, dimension-order XY rerouting is presented. In the second approach, a reconfigurable routing for Networks-on-Chip with logical hierarchy is proposed in which cross-layer interaction is used to enable hierarchical units to manage themselves autonomously and to reconfigure the routing. Both approaches are evaluated regarding their performance as well as their implementation costs. In a final study, the cross-layer diagnosis technique and cross-layer fault tolerance approaches are combined. The information obtained by the diagnosis technique is used by the fault tolerance approaches for packet rerouting or for routing reconfiguration. The combinations are evaluated regarding their impact on Networks-on-Chip performance. The results show that the crosslayer information exchange with software has a considerable impact on performance when the amount of information becomes too large. In case of crosslayer diagnosis, however, the impact on Networks-on-Chip performance is significantly lower compared to functional and structural diagnosis
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