GSFC Annual Scan Technology Review SpaceCube On-Board Processor Update

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Analysis and optimization of a debug post-silicon hardware architecture

The goal of this thesis is to analyze the post-silicon validation hardware infrastructure implemented on multicore systems taking as an example Esperanto Technologies SoC, which has thousands of RISC-V processors and targets specific software applications. Then, based on the conclusions of the analysis, the project proposes a new post-silicon debug architecture that can fit on any System on-Chip without depending on its target application or complexity and that optimizes the options available on the market for multicore systems

Virtual Timing Isolation Safety-Net for Multicore Processors

Multicore processors promise to offer the performance as well as the reduced space, weight and power needed by future aircrafts. However, commercial off-the-shelf multicore processors suffer from timing interferences between cores which complicates applying them in hard real-time systems like avionic applications. In this thesis, a safety-net system is proposed which enables a virtual timing isolation of applications running on one core from all other cores. The technique is based on hardware external to the multicore processor and completely transparent to the applications, i.e. no modification of the observed software is necessary. The basic idea is to apply a single-core execution based worst-case execution time analysis and to accept a predefined slowdown during multicore execution. If the slowdown exceeds the acceptable bounds, interferences will be reduced by controlling the behavior of low-critical cores to keep the main application’s progress inside the given bounds. Measuring the progress of the applications running on the main core is performed by tracking the application’s fingerprint. A fingerprint is created by extraction of the performance counters of the critical core in very small timesteps which results in a characteristic curve for every execution of a periodic program. In standalone mode, without any running applications on the other cores, a model of an application is created by clustering and combining the extracted curves. During runtime, the extracted performance counter values are compared to the model to determine the progress of the critical application. In case the progress of an application is unacceptably delayed, the cores creating the interferences are throttled. The interference creating cores are determined by the accesses of the respective cores to the shared resources. A controller that takes the progress of a critical application as well as the time until the final deadline into account throttles the low priority cores. Throttling is either performed by frequency scaling of the interfering cores or by halt and continue with a pulse width modulation scheme. The complete safety-net system was evaluated on a TACLeBench benchmark running on an NXP P4080 multicore processor observed by a Xilinx FPGA implementing a MicroBlaze soft-core microcontroller. The results show that the progress can be measured by the fingerprinting with a final deviation of less than 1% for a TACLeBench execution with running opponent cores and indicate the non-intrusiveness of the approach. Several experiments are conducted to demonstrate the effectiveness of the different throttling mechanisms. Evaluations using a real-world avionic application show that the approach can be applied to integrated modular avionic applications. The safety-net does not ensure robust partitioning in the conventional meaning. The applications on the different cores can influence each other in the timing domain, but the external safety-net ensures that the interference on the high critical application is low enough to keep the timing. This allows for an efficient utilization of the multicore processor. Every critical application is treated individually, and by relying on individual models recorded in standalone mode, the critical as well as the non-critical applications running on the other cores can be exchanged without recreating a fingerprint model. This eases the porting of legacy applications to the multicore processor and allows the exchange of applications without recertification.Der Einsatz von Multicore Prozessoren in Avioniksystemen verspricht sowohl die Performancesteigerung als auch den reduzierten Platz-, Gewichts- und Energieverbrauch, der zur Realisierung von zukünftigen Flugzeugen benötigt wird. Die Verwendung von seriengefertigten (COTS) Multicore Prozessoren in sicherheitskritischen Echtzeitsystemen ist jedoch sehr komplex, da eine gegenseitige zeitliche Beeinflussung der Anwendungen auf den unterschiedlichen Kernen nicht ausgeschlossen werden kann. In dieser Arbeit wird ein Konzept vorgestellt, das eine virtuelle zeitliche Trennung der Anwendungen, die auf einem Prozessorkern ausgeführt werden, von denen der übrigen Kerne ermöglicht. Die Grundidee besteht darin, eine auf einer Single-Core-Ausführung basierende Laufzeitanalyse (WCET) durchzuführen und eine vordefinierte Verlangsamung während der Multicore-Ausführung zu akzeptieren. Wenn die Verlangsamung die zulässige Grenze überschreitet, wird das Verhalten niedrigkritischer Kerne so gesteuert, dass der Fortschritt der Hauptanwendung innerhalb der Deadlines bleibt. Die Bestimmung des Fortschritts der kritischen Anwendungen erfolgt durch das Verfolgen eines sogenannten Fingerprints. Ein Fingerprint wird durch Auslesen der Performance Counter des kritischen Kerns in sehr kleinen Zeitschritten erzeugt, was zu einer charakteristischen Kurve für jede Ausführung eines periodischen Programms führt. Ein Modell einer Anwendung wird erstellt, indem die extrahierten Kurven gruppiert und kombiniert werden. Während der Laufzeit werden die ausgelesenen Werte mit dem Modell verglichen, um den Fortschritt zu bestimmen. Falls die zeitliche Ausführung einer ktitischen Anwendung zu stark verzögert wird, werden die Kerne gedrosselt, welche die Störungen verursachen. Das Konzept wurde mit einem TACLeBench-Benchmark evaluiert, der auf einem NXP P4080 Multicore Prozessor ausgefüht, und von einem Xilinx-FPGA beobachtet wurde. Es konnte gezeigt werden, dass der Fortschritt durch den Fingerprint mit einer endgültigen Abweichung von weniger als 1% für eine TACLeBench-Ausführung mit laufenden konkurrierenden Kernen gemessen werden kann. Die Evaluation mit einer realen Avionik-Anwendung zeigte, dass das Konzept für integrierte modulare Avionik-Anwendungen (IMA) genutzt werden kann. Der Ansatz gewährleistet keine robuste Partitionierung im herkömmlichen Sinne. Die Anwendungen auf den verschiedenen Kernen können sich zeitlich gegenseitig beeinflussen, aber ein externes Sicherheitsnetz stellt sicher, dass die Verlangsamung der hochkritischen Anwendung niedrig genug ist, um die Deadlines zu halten. Dies ermöglicht eine effiziente Auslastung des Multicore Prozessors. Außerdem wird jede kritische Anwendung einzeln behandelt und verfügt über ein individuelles Modell. Somit können die kritischen und nicht kritischen Anwendungen, die auf den anderen Kernen ausgeführt werden, ausgetauscht werden, ohne ein Modell neu zu erstellen. Dies vereinfacht die Portierung von bestehenden Anwendungen auf Multicore Prozessoren und ermöglicht den Austausch von Anwendungen ohne eine erneute Zertifizierung

NASA SpaceCube Edge TPU SmallSat Card for Autonomous Operations and Onboard Science-Data Analysis

Using state-of-the-art artificial intelligence (AI)frameworks onboard spacecraft is challenging because common spacecraft processors cannot provide comparable performance to data centers with server-grade CPUs and GPUs available for terrestrial applications and advanced deep-learning networks. This limitation makes small, low-power AI microchip architectures, such as the Google Coral Edge Tensor Processing Unit (TPU), attractive for space missions where the application-specific design enables both high-performance and power-efficient computing for AI applications. To address these challenging considerations for space deployment, this research introduces the design and capabilities of a CubeSat-sized Edge TPU-based co-processor card, known as the SpaceCube Low-power Edge Artificial Intelligence Resilient Node (SC-LEARN). This design conforms to NASA’s CubeSat Card Specification (CS2) for integration into next-generation SmallSat and CubeSat systems. This paper describes the overarching architecture and design of the SC-LEARN, as well as, the supporting test card designed for rapid prototyping and evaluation. The SC-LEARN was developed with three operational modes: (1) a high-performance parallel-processing mode,(2)a fault-tolerant mode for onboard resilience, and (3) a power-saving mode with cold spares. Importantly, this research also elaborates on both training and quantization of TensorFlow models for the SC-LEARN for use onboard with representative, open-source datasets. Lastly, we describe future research plans, including radiation-beam testing and flight demonstration

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

The impact of design techniques in the reduction of power consumption of SoCs Multimedia

Orientador: Guido Costa Souza de AraújoDissertação (mestrado) - Universidade Estadual de Campinas, Instituto de ComputaçãoResumo: A indústria de semicondutores sempre enfrentou fortes demandas em resolver problema de dissipação de calor e reduzir o consumo de energia em dispositivos. Esta tendência tem sido intensificada nos últimos anos com o movimento de sustentabilidade ambiental. A concepção correta de um sistema eletrônico de baixo consumo de energia é um problema de vários níveis de complexidade e exige estratégias sistemáticas na sua construção. Fora disso, a adoção de qualquer técnica de redução de energia sempre está vinculada com objetivos especiais e provoca alguns impactos no projeto. Apesar dos projetistas conheçam bem os impactos de forma qualitativa, as detalhes quantitativas ainda são incógnitas ou apenas mantidas dentro do 'know-how' das empresas. Neste trabalho, de acordo com resultados experimentais baseado num plataforma de SoC1 industrial, tentamos quantificar os impactos derivados do uso de técnicas de redução de consumo de energia. Nos concentramos em relacionar o fator de redução de energia de cada técnica aos impactos em termo de área, desempenho, esforço de implementação e verificação. Na ausência desse tipo de dados, que relacionam o esforço de engenharia com as metas de consumo de energia, incertezas e atrasos serão frequentes no cronograma de projeto. Esperamos que este tipo de orientações possam ajudar/guiar os arquitetos de projeto em selecionar as técnicas adequadas para reduzir o consumo de energia dentro do alcance de orçamento e cronograma de projetoAbstract: The semiconductor industry has always faced strong demands to solve the problem of heat dissipation and reduce the power consumption in electronic devices. This trend has been increased in recent years with the action of environmental sustainability. The correct conception of an electronic system for low power consumption is an issue with multiple levels of complexities and requires systematic approaches in its construction. However, the adoption of any technique for reducing the power consumption is always linked with some specific goals and causes some impacts on the project. Although the designers know well that these impacts can affect the design in a quality aspect, the quantitative details are still unkown or just be kept inside the company's know-how. In this work, according to the experimental results based on an industrial SoC2 platform, we try to quantify the impacts of the use of low power techniques. We will relate the power reduction factor of each technique to the impact in terms of area, performance, implementation and verification effort. In the absence of such data, which relates the engineering effort to the goals of power consumption, uncertainties and delays are frequent. We hope that such guidelines can help/guide the project architects in selecting the appropriate techniques to reduce the power consumption within the limit of budget and project scheduleMestradoCiência da ComputaçãoMestre em Ciência da Computaçã

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

Resource-efficient processing of large data volumes

The complex system environment of data processing applications makes it very challenging to achieve high resource efficiency. In this thesis, we develop solutions that improve resource efficiency at multiple system levels by focusing on three scenarios that are relevant—but not limited—to database management systems. First, we address the challenge of understanding complex systems by analyzing memory access characteristics via efficient memory tracing. Second, we leverage information about memory access characteristics to optimize the cache usage of algorithms and to avoid cache pollution by applying hardware-based cache partitioning. Third, after optimizing resource usage within a multicore processor, we optimize resource usage across multiple computer systems by addressing the problem of resource contention for bulk loading, i.e., ingesting large volumes of data into the system. We develop a distributed bulk loading mechanism, which utilizes network bandwidth and compute power more efficiently and improves both bulk loading throughput and query processing performance