598 research outputs found

    Automated Debugging Methodology for FPGA-based Systems

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    Electronic devices make up a vital part of our lives. These are seen from mobiles, laptops, computers, home automation, etc. to name a few. The modern designs constitute billions of transistors. However, with this evolution, ensuring that the devices fulfill the designer’s expectation under variable conditions has also become a great challenge. This requires a lot of design time and effort. Whenever an error is encountered, the process is re-started. Hence, it is desired to minimize the number of spins required to achieve an error-free product, as each spin results in loss of time and effort. Software-based simulation systems present the main technique to ensure the verification of the design before fabrication. However, few design errors (bugs) are likely to escape the simulation process. Such bugs subsequently appear during the post-silicon phase. Finding such bugs is time-consuming due to inherent invisibility of the hardware. Instead of software simulation of the design in the pre-silicon phase, post-silicon techniques permit the designers to verify the functionality through the physical implementations of the design. The main benefit of the methodology is that the implemented design in the post-silicon phase runs many order-of-magnitude faster than its counterpart in pre-silicon. This allows the designers to validate their design more exhaustively. This thesis presents five main contributions to enable a fast and automated debugging solution for reconfigurable hardware. During the research work, we used an obstacle avoidance system for robotic vehicles as a use case to illustrate how to apply the proposed debugging solution in practical environments. The first contribution presents a debugging system capable of providing a lossless trace of debugging data which permits a cycle-accurate replay. This methodology ensures capturing permanent as well as intermittent errors in the implemented design. The contribution also describes a solution to enhance hardware observability. It is proposed to utilize processor-configurable concentration networks, employ debug data compression to transmit the data more efficiently, and partially reconfiguring the debugging system at run-time to save the time required for design re-compilation as well as preserve the timing closure. The second contribution presents a solution for communication-centric designs. Furthermore, solutions for designs with multi-clock domains are also discussed. The third contribution presents a priority-based signal selection methodology to identify the signals which can be more helpful during the debugging process. A connectivity generation tool is also presented which can map the identified signals to the debugging system. The fourth contribution presents an automated error detection solution which can help in capturing the permanent as well as intermittent errors without continuous monitoring of debugging data. The proposed solution works for designs even in the absence of golden reference. The fifth contribution proposes to use artificial intelligence for post-silicon debugging. We presented a novel idea of using a recurrent neural network for debugging when a golden reference is present for training the network. Furthermore, the idea was also extended to designs where golden reference is not present

    Post-Silicon General Bus Function Model Modelling Approach Using C Code For Test Scheme Reuse And Sharing

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    Short product life cycle of a semiconductor IC is crucial for a company to gain better market share. But current validation process has become one of the bottleneck in semiconductor IC development process, where enhancement in this area can reduce the product lead time to market. There is a gap between pre- and post-silicon where both area is doing similar things but in different environment. A way to bridge the gap is by using the same test scheme which is applicable for both environment. This paper discuss and come out with an approach on how to model post-silicon BFM using high level programming language (C code) that is capable of content sharing and reuse between both pre- and post-silicon validation. Two methods to model post-silicon BFM are being approached and the more suitable one is being selected. The comparison is done is aspect of meeting strict timing requirement in sending signal. A prototype model of the selected model, which is second model is developed and tested in post-silicon validation environment to prove validity of the design. Test content in C code is created and synthesize into FPGA, act as stimulus generator for validation. The BFM device bit-accuracy behavior of the modelled Audio bus protocol is checked with waveform and signal trace. With this working model for developing BFM, pre- and post-silicon validation can share the same test scheme, saving efforts and time of developing test devices

    Virtual Cycle-accurate Hardware and Software Co-simulation Platform for Cellular IoT

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    Modern embedded development flows often depend on FPGA board usage for pre-ASIC system verification. The purpose of this project is to instead explore the usage of Electronic System Level (ESL) hardware-software co-simulation through the usage of ARM SoC Designer tool to create a virtual prototype of a cellular IoT modem and thereafter compare the benefits of including such a methodology into the early development cycle. The virtual system is completely developed and executed on a host computer, without the requirement of additional hardware. The virtual prototype hardware is based on C++ ARM verified cycle-accurate models generated from RTL hardware descriptions, High-level synthesis (HLS) pre-synthesis SystemC HW accelerator models and behavioural models which implement the ARM Cycle-accurate Simulation Interface (CASI). The micro-controller of the virtual system which is based on an ARM Cortex-M processor, is capable of executing instructions from a memory module. This report documents the virtual prototype implementation and compares both the software performance and cycle-accuracy of various virtual micro-controller configurations to a commercial reference development board. By altering factors such as memory latencies and bus interconnect subsystem arbitration in co-simulations, the software cycle-count performance of the development board was shown possible to reproduce within a 5% error margin, at the cost of approximately 266 times slower execution speed. Furthermore, the validity of two HLS pre-synthesis hardware models is investigated and proven to be functionally accurate within three clock cycles of individual block latency compared to post-synthesis FPGA synthesized implementations. The final virtual prototype system consisted of the micro-controller and two cellular IoT hardware accelerators. The system runs a FreeRTOS 9.0.0 port, executing a multi-threaded program at an average clock cycle simulation frequency of 10.6 kHz.-Designing and simulating embedded computer systems virtually. Cellular internet of things (IoT) is a new technology that will enable the interconnection of everything: from street lights and parking meters to your gas or water meter at home, wireless cellular networks will allow information to be shared between devices. However, in order for these systems to provide any useful data, they need to include a computer chip with a system to manage the communication itself, enabling the connection to a cellular network and the actual transmission and reception of data. Such a chip is called an embedded chip or system. Traditionally, the design and verification of digital embedded systems, that is to say a system which has both hardware and software components, had to be done in two steps. The first step consists of designing all the hardware, testing it, integrating it and producing it physically on silicon in order to verify the intended functionality of all the components. The second step thus consists of taking the hardware that has been developed and designing the software: a program which will have to execute in complete compliance to the hardware that has been previously developed. This poses two main issues: the software engineers cannot begin their work properly until the hardware is finished, which makes the process very long, and the fact that the hardware has been printed on silicon greatly restricts the possibility of doing changes to accommodate late system requirement alterations; which is quite likely for a tailor-made application specific system such as a cellular IoT chip. A currently widespread technology used to mitigate the previously mentioned negative aspects of embedded design, is the employment of field-programmable gate array (FPGA) development boards which often contain a micro-controller (with a processor and some memories), and a gate array connected to it. The FPGA part consists of a lattice of digital logic gates which can be programmed to interconnect and represent the functionality of the hardware being designed. The processor can thus execute software instructions placed on the memories and the hardware being developed can be programmed into the gate array in order to integrate and verify a full hardware and software system. Nevertheless, this boards are expensive and limit the design to the hardware components available commercially in the different off-the-shelf models, e.g. a specific processor which might not be the desired one. Now imagine there is a way to design hardware components such as processors in the traditional way, however once the hardware has been implemented it can be integrated together with software without the need of printing a physical silicon chip specifically for this purpose. That would be extremely convenient and would save lots of time, would it not? Fortunately, this is already possible due to Electronic System Level (ESL) design, which is compilation of techniques that allow to design, simulate and partially verify a digital chip, all within any normal laptop or desktop computer. Moreover, some ESL tools such as the one investigated in this project, allow you to even simulate a program code written specifically for this hardware; this is known as virtual hardware software co-simulation. The reliability of simulation must however be considered when compared to a traditional two-step methodology or FPGA board usage to verify a full system. This is because a virtual hardware simulation can have several degrees of accuracy, depending on the specificity of component models that make up the virtual prototype of the digital system. Therefore, in order to use co-simulation techniques with a high degree of confidence for verification, the highest accuracy degree should be employed if possible to guarantee that what is being simulated will match the reality of a silicon implementation. The clock cycle-accurate level is one of the highest accuracy system simulation methods available, and it consists of representing the digital states of all hardware components such as signals and registers, in a cycle-by-cycle manner. By using the ARM SoC Designer ESL tool, we have co-designed and co-simulated several microcontrollers on a detailed, cycle-accurate level and confirmed its behaviour by comparing it to a physical reference target development board. Finally, a more complex virtual prototype of a cellular IoT system was also simulated, including a micro-controller running a a real-time operating system (RTOS), hardware accelerators and serial data interfacing. Parts of this virtual prototype where compared to an FPGA board to evaluate the pros and cons of incorporating virtual system simulation into the development cycle and to what extent can ESL methods substitute traditional verification techniques. The ease of interchanging hardware, simplicity of development, simulation speed and the level of debug capabilities available when developing in a virtual environment are some of the aspects of ARM SoC Designer discussed in this thesis. A more in depth description of the methodology and results can be found in the report titled "Virtual Cycle-accurate Hardware and Software Co-simulation Platform for Cellular IoT"

    Architectures for dependable modern microprocessors

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    Η εξέλιξη των ολοκληρωμένων κυκλωμάτων σε συνδυασμό με τους αυστηρούς χρονικούς περιορισμούς καθιστούν την επαλήθευση της ορθής λειτουργίας των επεξεργαστών μία εξαιρετικά απαιτητική διαδικασία. Με κριτήριο το στάδιο του κύκλου ζωής ενός επεξεργαστή, από την στιγμή κατασκευής των πρωτοτύπων και έπειτα, οι τεχνικές ελέγχου ορθής λειτουργίας διακρίνονται στις ακόλουθες κατηγορίες: (1) Silicon Debug: Τα πρωτότυπα ολοκληρωμένα κυκλώματα ελέγχονται εξονυχιστικά, (2) Manufacturing Testing: ο τελικό ποιοτικός έλεγχος και (3) In-field verification: Περιλαμβάνει τεχνικές, οι οποίες διασφαλίζουν την λειτουργία του επεξεργαστή σύμφωνα με τις προδιαγραφές του. Η διδακτορική διατριβή προτείνει τα ακόλουθα: (1) Silicon Debug: Η εργασία αποσκοπεί στην επιτάχυνση της διαδικασίας ανίχνευσης σφαλμάτων και στον αυτόματο εντοπισμό τυχαίων προγραμμάτων που δεν περιέχουν νέα -χρήσιμη- πληροφορία σχετικά με την αίτια ενός σφάλματος. Η κεντρική ιδέα αυτής της μεθόδου έγκειται στην αξιοποίηση της έμφυτης ποικιλομορφίας των αρχιτεκτονικών συνόλου εντολών και στην δυνατότητα από-διαμόρφωσης τμημάτων του κυκλώματος, (2) Manufacturing Testing: προτείνεται μία μέθοδο για την βελτιστοποίηση του έλεγχου ορθής λειτουργίας των πολυνηματικών και πολυπύρηνων επεξεργαστών μέσω της χρήση λογισμικού αυτοδοκιμής, (3) Ιn-field verification: Αναλύθηκε σε βάθος η επίδραση που έχουν τα μόνιμα σφάλματα σε μηχανισμούς αύξησης της απόδοσης. Επιπρόσθετα, προτάθηκαν τεχνικές για την ανίχνευση και ανοχή μόνιμων σφαλμάτων υλικού σε μηχανισμούς πρόβλεψης διακλάδωσης.Technology scaling, extreme chip integration and the compelling requirement to diminish the time-to-market window, has rendered microprocessors more prone to design bugs and hardware faults. Microprocessor validation is grouped into the following categories, based on where they intervene in a microprocessor’s lifecycle: (a) Silicon debug: the first hardware prototypes are exhaustively validated, (b) Μanufacturing testing: the final quality control during massive production, and (c) In-field verification: runtime error detection techniques to guarantee correct operation. The contributions of this thesis are the following: (1) Silicon debug: We propose the employment of deconfigurable microprocessor architectures along with a technique to generate self-checking random test programs to avoid the simulation step and triage the redundant debug sessions, (2) Manufacturing testing: We propose a self-test optimization strategy for multithreaded, multicore microprocessors to speedup test program execution time and enhance the fault coverage of hard errors; and (3) In-field verification: We measure the effect of permanent faults performance components. Then, we propose a set of low-cost mechanisms for the detection, diagnosis and performance recovery in the front-end speculative structures. This thesis introduces various novel methodologies to address the validation challenges posed throughout the life-cycle of a chip

    A study on Machine Learning-based Hardware Bug Localization

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    Simulation-based verification is a very essential technique in ensuring the correct functionality of any digital integrated circuit design before it goes on silicon. One of the major challenges of running simulation-based verification on complex designs is the tradeoff between simulation time and the time taken for failure localization or to root cause. This is because the simulation run times could be very high when there are many checkers used per cycle of execution. However, when lesser checkers are turned on, the amount of time for manual debug increases because, after failure, the verification engineer has to manually analyze the failure and turn on the more granular checkers individually and re-simulate; or invest lots of time, memory and resources to manually go through the simulation cycles dumps before the failure which is not good given the current complexity of designs. Machine learning has emerged to be a popular technique to construct mathematical models that can understand the expected patterns from a given dataset. To address the aforementioned trade-off problem, an idea is investigated to use the failing signatures from fewer active high-level checkers during simulation to train a machine learning model to predict the location of the bug in the design. This information would in turn be used to turn on relevant checkers in the design before re-simulation. Other methods to analyze the signals in design after failure to predict bug location were also studied. This idea is implemented and tested on a MIPS processor with total of ~ 700 bugs injected in 15 different units to distinguish them with good accuracy

    Observation mechanisms for in-field software-based self-test

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    When electronic systems are used in safety critical applications, as in the space, avionic, automotive or biomedical areas, it is required to maintain a very low probability of failures due to faults of any kind. Standards and regulations play a significant role, forcing companies to devise and adopt solutions able to achieve predefined targets in terms of dependability. Different techniques can be used to reduce fault occurrence or to minimize the probability that those faults produce critical failures (e.g., by introducing redundancy). Unfortunately, most of these techniques have a severe impact on the cost of the resulting product and, in some cases, the probability of failures is too large anyway. Hence, a solution commonly used in several scenarios lies on periodically performing a test able to detect the occurrence of any fault before it produces a failure (in-field test). This solution is normally based on forcing the processor inside the Device Under Test to execute a properly written test program, which is able to activate possible faults and to make their effects visible in some observable locations. This approach is also called Software-Based Self-Test, or SBST. If compared with testing in an end of manufacturing scenario, in-field testing has strong limitations in terms of access to the system inputs and outputs because Design for Testability structures and testing equipment are usually not available. As a consequence there are reduced possibilities to activate the faults and to observe their effects. This reduced observability particularly affects the ability to detect performance faults, i.e. faults that modify the timing but not the final value of computations. This kind of faults are hard to detect by only observing the final content of predefined memory locations, that is the usual test result observation method used in-field. Initially, the present work was focused on fault tolerance techniques against transient faults induced by ionizing radiation, the so called Single Event Upsets (SEUs). The main contribution of this early stage of the thesis lies in the experimental validation of the feasibility of achieving a safe system by using an architecture that combines task-level redundancy with already available IP cores, thus minimizing the development time. Task execution is replicated and Memory Protection is used to guarantee that any SEU may affect one and only one of the replicas. A proof of concept implementation was developed and validated using fault injection. Results outline the effectiveness of the architecture, and the overhead analysis shows that the proposed architecture is effective in reducing the resource occupation with respect to N-modular redundancy, at an affordable cost in terms of application execution time. The main part of the thesis is focused on in-field software-based self-test of permanent faults. A set of observation methods exploiting existing or ad-hoc hardware is proposed, aimed at obtaining a better coverage, in particular of performance faults. An extensive quantitative evaluation of the proposed methods is presented, including a comparison with the observation methods traditionally used in end of manufacturing and in-field testing. Results show that the proposed methods are a good complement to the traditionally used final memory content observation. Moreover, they show that an adequate combination of these complementary methods allows for achieving nearly the same fault coverage achieved when continuously observing all the processor outputs, which is an observation method commonly used for production test but usually not available in-field. A very interesting by-product of what is described above is a detailed description of how to compute the fault coverage achieved by functional in-field tests using a conventional fault simulator, a tool that is usually applied in an end of manufacturing testing scenario. Finally, another relevant result in the testing area is a method to detect permanent faults inside the cache coherence logic integrated in each cache controller of a multi-core system, based on the concurrent execution of a test program by the different cores in a coordinated manner. By construction, the method achieves full fault coverage of the static faults in the addressed logic.Cuando se utilizan sistemas electrónicos en aplicaciones críticas como en las áreas biomédica, aeroespacial o automotriz, se requiere mantener una muy baja probabilidad de malfuncionamientos debidos a cualquier tipo de fallas. Los estándares y normas juegan un papel importante, forzando a los desarrolladores a diseñar y adoptar soluciones que sean capaces de alcanzar objetivos predefinidos en cuanto a seguridad y confiabilidad. Pueden utilizarse diferentes técnicas para reducir la ocurrencia de fallas o para minimizar la probabilidad de que esas fallas produzcan mal funcionamientos críticos, por ejemplo a través de la incorporación de redundancia. Lamentablemente, muchas de esas técnicas afectan en gran medida el costo de los productos y, en algunos casos, la probabilidad de malfuncionamiento sigue siendo demasiado alta. En consecuencia, una solución usada a menudo en varios escenarios consiste en realizar periódicamente un test que sea capaz de detectar la ocurrencia de una falla antes de que esta produzca un mal funcionamiento (test en campo). En general, esta solución se basa en forzar a un procesador existente dentro del dispositivo bajo prueba a ejecutar un programa de test que sea capaz de activar las posibles fallas y de hacer que sus efectos sean visibles en puntos observables. A esta metodología también se la llama auto-test basado en software, o en inglés Software-Based Self-Test (SBST). Si se lo compara con un escenario de test de fin de fabricación, el test en campo tiene fuertes limitaciones en términos de posibilidad de acceso a las entradas y salidas del sistema, porque usualmente no se dispone de equipamiento de test ni de la infraestructura de Design for Testability. En consecuencia se tiene menos posibilidades de activar las fallas y de observar sus efectos. Esta observabilidad reducida afecta particularmente la habilidad para detectar fallas de performance, es decir fallas que modifican la temporización pero no el resultado final de los cálculos. Este tipo de fallas es difícil de detectar por la sola observación del contenido final de lugares de memoria, que es el método usual que se utiliza para observar los resultados de un test en campo. Inicialmente, el presente trabajo estuvo enfocado en técnicas para tolerar fallas transitorias inducidas por radiación ionizante, llamadas en inglés Single Event Upsets (SEUs). La principal contribución de esa etapa inicial de la tesis reside en la validación experimental de la viabilidad de obtener un sistema seguro, utilizando una arquitectura que combina redundancia a nivel de tareas con el uso de módulos hardware (IP cores) ya disponibles, que minimiza en consecuencia el tiempo de desarrollo. Se replica la ejecución de las tareas y se utiliza protección de memoria para garantizar que un SEU pueda afectar a lo sumo a una sola de las réplicas. Se desarrolló una implementación para prueba de concepto que fue validada mediante inyección de fallas. Los resultados muestran la efectividad de la arquitectura, y el análisis de los recursos utilizados muestra que la arquitectura propuesta es efectiva en reducir la ocupación con respecto a la redundancia modular con N réplicas, a un costo accesible en términos de tiempo de ejecución. La parte principal de esta tesis se enfoca en el área de auto-test en campo basado en software para la detección de fallas permanentes. Se propone un conjunto de métodos de observación utilizando hardware existente o ad-hoc, con el fin de obtener una mejor cobertura, en particular de las fallas de performance. Se presenta una extensa evaluación cuantitativa de los métodos propuestos, que incluye una comparación con los métodos tradicionalmente utilizados en tests de fin de fabricación y en campo. Los resultados muestran que los métodos propuestos son un buen complemento del método tradicionalmente usado que consiste en observar el valor final del contenido de memoria. Además muestran que una adecuada combinación de estos métodos complementarios permite alcanzar casi los mismos valores de cobertura de fallas que se obtienen mediante la observación continua de todas las salidas del procesador, método comúnmente usado en tests de fin de fabricación, pero que usualmente no está disponible en campo. Un subproducto muy interesante de lo arriba expuesto es la descripción detallada del procedimiento para calcular la cobertura de fallas lograda mediante tests funcionales en campo por medio de un simulador de fallas convencional, una herramienta que usualmente se aplica en escenarios de test de fin de fabricación. Finalmente, otro resultado relevante en el área de test es un método para detectar fallas permanentes dentro de la lógica de coherencia de cache que está integrada en el controlador de cache de cada procesador en un sistema multi procesador. El método está basado en la ejecución de un programa de test en forma coordinada por parte de los diferentes procesadores. Por construcción, el método cubre completamente las fallas de la lógica mencionad

    Embedded Firmware Solutions

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    Computer scienc

    Fault Tolerant Electronic System Design

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    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
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