Automated Debugging Methodology for FPGA-based Systems

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

Using embedded hardware monitor cores in critical computer systems

The integration of FPGA devices in many different architectures and services makes monitoring and real time detection of errors an important concern in FPGA system design. A monitor is a tool, or a set of tools, that facilitate analytic measurements in observing a given system. The goal of these observations is usually the performance analysis and optimisation, or the surveillance of the system. However, System-on-Chip (SoC) based designs leave few points to attach external tools such as logic analysers. Thus, an embedded error detection core that allows observation of critical system nodes (such as processor cores and buses) should enforce the operation of the FPGA-based system, in order to prevent system failures. The core should not interfere with system performance and must ensure timely detection of errors. This thesis is an investigation onto how a robust hardware-monitoring module can be efficiently integrated in a target PCI board (with FPGA-based application processing features) which is part of a critical computing system. [Continues.

Protocol-directed trace signal selection for post-silicon validation

Due to the increasing complexity of modern digital designs using NoC (network-on-chip) communication, post-silicon validation has become an arduous task that consumes much of the development time of the product. The process of finding the root cause of bugs during post-silicon validation is very difficult because of the lack of observability of all signals on the chip. To increase observability for post-silicon validation, an effective silicon debug technique is to use an on-chip trace buffer to monitor and capture the circuit response of certain selected signals during its post-silicon operation. However, because of area limitations for debug structures on chip and routing concerns, the signals that are selected to be traced are a very small subset of all available signals. Traditionally, these trace signals were chosen manually by system designers who determined what signals may be needed for debug once the design reaches post-silicon. However, because modern digital designs have become very complex with many concurrent processes, this method is no longer reliable. Recent work has concentrated on automating the selection of low-level signals from a gate-level analysis. But none of them has ever been able to interpret the trace signals as high-level meaningful debugging information. In this work, we present an automated protocol-directed trace selection where the guiding force is the set of system-level protocols. We use a probabilistic formulation to select messages for tracing and then further analyze these solutions. This method produces traces that allow a debugger to observe when behavior has deviated from the correct path of execution and localize this incorrect behavior for further analysis. Most importantly, unlike the previous gate-level analysis based methods, this method can be applied during the chip design phase when most of the debug features are also designed. In addition, this method drastically reduces the time needed to select signals, as we automate a currently manual process

Real-Time Trace Decoding and Monitoring for Safety and Security in Embedded Systems

Integrated circuits and systems can be found almost everywhere in today’s world. As their use increases, they need to be made safer and more perfor mant to meet current demands in processing power. FPGA integrated SoCs can provide the ideal trade-off between performance, adaptability, and energy usage. One of today’s vital challenges lies in updating existing fault tolerance techniques for these new systems while utilizing all available processing capa bilities, such as multi-core and heterogeneous processing units. Control-flow monitoring is one of the primary mechanisms described for error detection at the software architectural level for the highest grade of hazard level clas sifications (e.g., ASIL D) described in industry safety standards ISO-26262. Control-flow errors are also known to compose the majority of detected errors for ICs and embedded systems in safety-critical and risk-susceptible environ ments [5]. Software-based monitoring methods remain the most popular [6–8]. However, recent studies show that the overheads they impose make actual reliability gains negligible [9, 10]. This work proposes and demonstrates a new control flow checking method implemented in FPGA for multi-core embedded systems called control-flow trace checker (CFTC). CFTC uses existing trace and debug subsystems of modern processors to rebuild their execution states. It can iden tify any errors in real-time by comparing executed states to a set of permitted state transitions determined statically. This novel implementation weighs hardware resource trade-offs to target mul tiple independent tasks in multi-core embedded applications, as well as single core systems. The proposed system is entirely implemented in hardware and isolated from all monitored software components, requiring 2.4% of the target FPGA platform resources to protect an execution unit in its entirety. There fore, it avoids undesired overheads and maintains deterministic error detection latencies, which guarantees reliability improvements without impairing the target software system. Finally, CFTC is evaluated under different software i Resumo fault-injection scenarios, achieving detection rates of 100% of all control-flow errors to wrong destinations and 98% of all injected faults to program binaries. All detection times are further analyzed and precisely described by a model based on the monitor’s resources and speed and the software application’s control-flow structure and binary characteristics.Circuitos integrados estão presentes em quase todos sistemas complexos do mundo moderno. Conforme sua frequência de uso aumenta, eles precisam se tornar mais seguros e performantes para conseguir atender as novas demandas em potência de processamento. Sistemas em Chip integrados com FPGAs conseguem prover o balanço perfeito entre desempenho, adaptabilidade, e uso de energia. Um dos maiores desafios agora é a necessidade de atualizar técnicas de tolerância à falhas para estes novos sistemas, aproveitando os novos avanços em capacidade de processamento. Monitoramento de fluxo de controle é um dos principais mecanismos para a detecção de erros em nível de software para sistemas classificados como de alto risco (e.g. ASIL D), descrito em padrões de segurança como o ISO-26262. Estes erros são conhecidos por compor a maioria dos erros detectados em sistemas integrados [5]. Embora métodos de monitoramento baseados em software continuem sendo os mais populares [6–8], estudos recentes mostram que seus custos adicionais, em termos de performance e área, diminuem consideravelmente seus ganhos reais em confiabilidade [9, 10]. Propomos aqui um novo método de monitora mento de fluxo de controle implementado em FPGA para sistemas embarcados multi-core. Este método usa subsistemas de trace e execução de código para reconstruir o estado atual do processador, identificando erros através de com parações entre diferentes estados de execução da CPU. Propomos uma implementação que considera trade-offs no uso de recuros de sistema para monitorar múltiplas tarefas independetes. Nossa abordagem suporta o monitoramento de sistemas simples e também de sistemas multi-core multitarefa. Por fim, nossa técnica é totalmente implementada em hardware, evitando o uso de unidades de processamento de software que possa adicionar custos indesejáveis à aplicação em perda de confiabilidade. Propomos, assim, um mecanismo de verificação de fluxo de controle, escalável e extensível, para proteção de sistemas embarcados críticos e multi-core

Real-time trace decoding and monitoring for safety and security in embedded systems

Integrated circuits and systems can be found almost everywhere in today’s world. As their use increases, they need to be made safer and more perfor mant to meet current demands in processing power. FPGA integrated SoCs can provide the ideal trade-off between performance, adaptability, and energy usage. One of today’s vital challenges lies in updating existing fault tolerance techniques for these new systems while utilizing all available processing capa bilities, such as multi-core and heterogeneous processing units. Control-flow monitoring is one of the primary mechanisms described for error detection at the software architectural level for the highest grade of hazard level clas sifications (e.g., ASIL D) described in industry safety standards ISO-26262. Control-flow errors are also known to compose the majority of detected errors for ICs and embedded systems in safety-critical and risk-susceptible environ ments [5]. Software-based monitoring methods remain the most popular [6–8]. However, recent studies show that the overheads they impose make actual reliability gains negligible [9, 10]. This work proposes and demonstrates a new control flow checking method implemented in FPGA for multi-core embedded systems called control-flow trace checker (CFTC). CFTC uses existing trace and debug subsystems of modern processors to rebuild their execution states. It can iden tify any errors in real-time by comparing executed states to a set of permitted state transitions determined statically. This novel implementation weighs hardware resource trade-offs to target mul tiple independent tasks in multi-core embedded applications, as well as single core systems. The proposed system is entirely implemented in hardware and isolated from all monitored software components, requiring 2.4% of the target FPGA platform resources to protect an execution unit in its entirety. There fore, it avoids undesired overheads and maintains deterministic error detection latencies, which guarantees reliability improvements without impairing the target software system. Finally, CFTC is evaluated under different software i Resumo fault-injection scenarios, achieving detection rates of 100% of all control-flow errors to wrong destinations and 98% of all injected faults to program binaries. All detection times are further analyzed and precisely described by a model based on the monitor’s resources and speed and the software application’s control-flow structure and binary characteristics.Circuitos integrados estão presentes em quase todos sistemas complexos do mundo moderno. Conforme sua frequência de uso aumenta, eles precisam se tornar mais seguros e performantes para conseguir atender as novas demandas em potência de processamento. Sistemas em Chip integrados com FPGAs conseguem prover o balanço perfeito entre desempenho, adaptabilidade, e uso de energia. Um dos maiores desafios agora é a necessidade de atualizar técnicas de tolerância à falhas para estes novos sistemas, aproveitando os novos avanços em capacidade de processamento. Monitoramento de fluxo de controle é um dos principais mecanismos para a detecção de erros em nível de software para sistemas classificados como de alto risco (e.g. ASIL D), descrito em padrões de segurança como o ISO-26262. Estes erros são conhecidos por compor a maioria dos erros detectados em sistemas integrados [5]. Embora métodos de monitoramento baseados em software continuem sendo os mais populares [6–8], estudos recentes mostram que seus custos adicionais, em termos de performance e área, diminuem consideravelmente seus ganhos reais em confiabilidade [9, 10]. Propomos aqui um novo método de monitora mento de fluxo de controle implementado em FPGA para sistemas embarcados multi-core. Este método usa subsistemas de trace e execução de código para reconstruir o estado atual do processador, identificando erros através de com parações entre diferentes estados de execução da CPU. Propomos uma implementação que considera trade-offs no uso de recuros de sistema para monitorar múltiplas tarefas independetes. Nossa abordagem suporta o monitoramento de sistemas simples e também de sistemas multi-core multitarefa. Por fim, nossa técnica é totalmente implementada em hardware, evitando o uso de unidades de processamento de software que possa adicionar custos indesejáveis à aplicação em perda de confiabilidade. Propomos, assim, um mecanismo de verificação de fluxo de controle, escalável e extensível, para proteção de sistemas embarcados críticos e multi-core

Multilevel Runtime Verification for Safety and Security Critical Cyber Physical Systems from a Model Based Engineering Perspective

Advanced embedded system technology is one of the key driving forces behind the rapid growth of Cyber-Physical System (CPS) applications. CPS consists of multiple coordinating and cooperating components, which are often software-intensive and interact with each other to achieve unprecedented tasks. Such highly integrated CPSs have complex interaction failures, attack surfaces, and attack vectors that we have to protect and secure against. This dissertation advances the state-of-the-art by developing a multilevel runtime monitoring approach for safety and security critical CPSs where there are monitors at each level of processing and integration. Given that computation and data processing vulnerabilities may exist at multiple levels in an embedded CPS, it follows that solutions present at the levels where the faults or vulnerabilities originate are beneficial in timely detection of anomalies. Further, increasing functional and architectural complexity of critical CPSs have significant safety and security operational implications. These challenges are leading to a need for new methods where there is a continuum between design time assurance and runtime or operational assurance. Towards this end, this dissertation explores Model Based Engineering methods by which design assurance can be carried forward to the runtime domain, creating a shared responsibility for reducing the overall risk associated with the system at operation. Therefore, a synergistic combination of Verification & Validation at design time and runtime monitoring at multiple levels is beneficial in assuring safety and security of critical CPS. Furthermore, we realize our multilevel runtime monitor framework on hardware using a stream-based runtime verification language

Performance Debugging Frameworks for FPGA High-Level Synthesis

Using high-level synthesis (HLS) tools for field-programmable gate array (FPGA) design is becoming an increasingly popular choice because HLS tools can generate a high-quality design in a short development time. However, current HLS tools still cannot adequately support users in understanding and fixing the performance issues of the current design. That is, current HLS tools lack in performance debugging capability. Previous work on performance debugging automates the process of inserting hardware monitors in low-level register-transfer level (RTL) languages which limits the comprehensibility of the obtained result. Instead, our HLS-based flows offer analysis on a function or loop level and provide more intuitive feedback that can be used to pinpoint the performance bottleneck of a design. In this dissertation, we present a collection of HLS-based debugging frameworks for various purposes and characteristics of the design. First, we address the problem in the HLS synthesis step, where an inaccurate cycle estimation is provided if the program has input-dependent behavior. We propose a new performance estimator that automatically instruments code that models the hardware execution behavior and interprets the information from the HLS software simulation. However, the performance estimation result of this flow may not be accurate for a type of designs that cannot be simulated correctly by existing HLS software simulators. To handle such cases, we propose a new software simulator that provides cycle-accurate result based on the HLS scheduling information. If the input dataset is not available for software simulation or high-level models do not exist for all components of the FPGA design, we also present an on-board monitoring flow for automated cycle extraction and stall analysis. Finally, we address the needs of HLS programmers to automatically find the best set of directives for FPGA designs. We propose a design space exploration (DSE) framework to optimize applications with variable loop bounds in Polybench benchmark. A quantitative comparison among the proposed frameworks is shown using the sparse matrix-vector multiplication benchmark