Exploring the Impact of Soft Errors on the Reliability of Real-Time Embedded Operating Systems

Abstract

The continuous scaling of electronic components has led to the development of high-performance microprocessors that are suitable even for safety-critical applications where radiation-induced errors such as Single Event Effects (SEEs) can have a significant impact on the performance and reliability of the system. This work is dedicated to investigating the reliability of systems based on programmable hardware and Real-time operating Systems (RTOS) in the presence of architectural faults induced by soft errors in the configuration memory of the programmable hardware. We performed a proton radiation test campaigned at PSI radiation facility to identify the fault model affecting the configuration memory of Xilinx Zynq-7020 reconfigurable AP-Soc Device. The identified fault model in terms of SEU and MBU clusters has been used to evaluate the impact of proton-induced faults on applications running within FreeRTOS on a Microblaze soft processor. A Single Event Multiple Upset fault model resulting from a proton test is presented, focusing on characteristics such as shape, size, and frequency of observed cluster of errors. We conduct two fault injection campaigns and analyze the results to assess the effect of cluster size on system reliability. Moreover, we discuss software exceptions caused by faults that can affect the hardware structure of the soft processor.

Machine Learning-Based Soft-Error-Rate Evaluation for Large-Scale Integrated Circuits

“…The BPNN model is used to calculate the pulse propagation probabilities in circuits A, B, and C. The calculated results are compared with the transient pulse propagation probabilities simulated by the circuit-level simulation tool. The prediction accuracy is calculated using Equation (10) and the results are shown in Table 4. The average prediction accuracy of the three test circuits is approximately 0.8.…”

“…In total, 60% of the data was used to train the BPNN model, and the remainder was used for model validation. The prediction accuracy of the model is calculated using the Equation (10). P represents the precision value of the prediction.…”

“…The collected electron-hole pairs produce unexpected transient pulses in circuit nodes [7]. These transient pulses propagate along the circuit path and cause soft errors [8][9][10]. A soft error is a significant threat to integrated circuits.…”