Recent research has shown interest in adopting the RISC-V processors for high-reliability electronics, such as aerospace applications. The openness of this architecture enables the implementation and customization of the processor features to increase their reliability. Studies on hardened RISC-V processors facing harsh radiation environments apply fault tolerance techniques in the processor core and peripherals, exploiting system redundancies. In prior work, we present a hardened RISC-V System-on-Chip (SoC), which could detect and correct radiation-induced faults with limited fault awareness. Therefore, in this work, we propose solutions to extend the fault observability of the SoC implementation by providing error detection and monitoring. For this purpose, we introduce observation features in the redundant structures of the system, enabling the report of valuable information that supports enhanced radiation testing and support the application to perform actions to recover from critical failures. Thus, the main contribution of this work is a solution to improve fault awareness and the analysis of the fault models in the system. In order to validate this solution, we performed complementary experiments in two irradiation facilities, comprehending atmospheric neutrons and a mixed-field environment, in which the system proved to be valuable for analyzing the radiation effects on the processor core and its peripherals. In these experiments, we were able to obtain a range of error reports that allowed us to gain a deeper understanding of the faults mechanisms, as well as improve the characterization of the SoC.

Modern space applications are increasingly demanding reliable processing systems with high computational capabilities for missions with ambitious targets, tight budgets, and fast deployment. Hence, the space sector is accelerating the adoption of Commercial Off-The-Shelf (COTS) high-performance and reconfigurable processors. In this context, we propose the analysis and characterization of software applications’ reliability on a novel RISC-V-based processing system: Microchip’s PolarFire System-on-Chip (SoC). For that, we introduce reliability benchmarks using baremetal and FreeRTOS implementations and perform an experimental evaluation using high-energy protons, reporting Single-Event Effects (SEE) cross sections and the impact of Total Ionizing Dose (TID). Moreover, we discuss in detail the error propagation and masking, proposing a reliability metric to support the standardization of radiation effects reporting on complex processing systems. Finally, we evaluate the effectiveness of error mitigation and awareness in PolarFire SoC using built-in monitoring and test instrumentation with enhanced observability.

The New Space era has driven a wide array of applications in novel space missions with an increasing demand for processors with high computational capabilities while simultaneously maintaining low power consumption, flexibility, and reliability. Soft-core processors based on Commercial Off-The-Shelf (COTS) technologies have emerged as a viable alternative that can meet these requirements but need to be hardened to operate in harsh environments. In this work, we propose and apply fault tolerance strategies based on software recovery using checkpoint and rollback operations to extend the capabilities of a hardened soft-core RISC-V-based System-on-Chip. The proposed strategy relies on the fault awareness provided by the SoC hardening to trigger the software recovery without the addition of dedicated structures or processor cores. Notably, we investigate the effectiveness of this multilayer hardening strategy, which combines software recoverability and hardware redundancy. For that, a neutron irradiation campaign was performed. The results show the effectiveness of the proposed approach, achieving 45.09% of effective software recovery operations with low overhead for performance and resource utilization.

Ionizing radiation induces the degradation of electronic systems. For memory devices, this phenomenon is often observed as the corruption of the stored data and, in some cases, the occurrence of sudden increases in current consumption during the operation. In this work, we propose enhanced experimental instrumentation to perform in-depth Single-Event Effects (SEE) monitoring and analysis of electronic systems. In particular, we focus on the Single-Event Latch-up (SEL) phenomena in memory devices, in which current monitoring and control are required for testing. To expose the features and function of the proposed instrumentation, we present results for a case study of an SRAM memory that has been used on-board PROBA-V ESA satellite. For this study, we performed experimental campaigns in two different irradiation facilities with protons and heavy ions, demonstrating the instrumentation capabilities, such as synchronization, high sampling rate, fast response time, and flexibility. Using this instrumentation, we could report the cross section for the observed SEEs and further investigate their correlation with the observed current behavior. Notably, it allowed us to identify that 95% of Single-Event Functional Interrupts (SEFIs) were triggered during SEL events.

Artificial neural networks (ANNs) have become essential components in various safety-critical applications, including autonomous vehicles, medical devices, and avionics, where system failures can lead to severe risks. Edge AI devices, which process data locally without relying on the cloud, are increasingly used to meet the performance and real-time demands of these applications. However, their reliability in radiation-prone environments is a significant concern. In this context, this paper evaluates the MAX78000, an ultra-low-power Edge AI microcontroller with a hardware-based convolutional neural network (CNN) accelerator, focusing on its behavior in radiation environments. To assess the reliability of the MAX78000, we performed a test campaign at the ChipIR neutron irradiation facility using two different ANNs. We implemented techniques to improve system observability during ANN inference and analyzed the radiation-induced errors observed. The results present a comparative analysis between the two ANN architectures, which shows that the complexity of the ANN directly impacts its reliability.

This work investigates the flight behavior of Static Random-Access Memories (SRAMs) on board the PROBA-V satellite. During the mission, unexpected error rates were observed for redundant modules that used Commercial Off-The-Shelf (COTS) SRAMs. After undergoing an initial assessment, it was inferred that these errors were caused by Single-Event Latch-ups (SELs). This result led to a broader study on Single-Event Effects (SEEs) in these SRAM devices and their impact on the PROBA-V operation. Therefore, we proposed an experimental approach for evaluating and comparing the phenomena with the available PROBA-V flight data. Three experiments were performed: two irradiation campaigns, using heavy ions and protons, and laser testing. For that, a dedicated experimental setup was developed to enable the evaluation of specific test conditions and the discussion of hypotheses. The main results are reported, compared, and discussed. As an outcome of this study, we proposed an explanation for the observed behavior due to distinct environmental conditions of the redundant modules containing the SRAMs, notably temperature and satellite shielding.