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Abstract-Software-based techniques offer several advantages to increase the reliability of processor-based systems at very low cost, but they cause performance degradation and an increase of the code size. To meet constraints in performance and memory, we propose SETA, a new control-flow software-only technique that uses assertions to detect errors affecting the program flow. SETA is an independent technique, but it was conceived to work together with previously proposed data-flow techniques that aim at reducing performance and memory overheads. Thus, SETA is combined with such data-flow techniques and submitted to a fault injection campaign. Simulation and neutron induced SEE tests show high fault coverage at performance and memory overheads inferior to the state-of-the-art.

This work is a survey on approximate computing and its impact on fault tolerance, especially for safety-critical applications. It presents a multitude of approximation methodologies, which are typically applied at software, architecture, and circuit level. Those methodologies are discussed and compared on all their possible levels of implementations (some techniques are applied at more than one level). Approximation is also presented as a means to provide fault tolerance and high reliability: Traditional error masking techniques, such as triple modular redundancy, can be approximated and thus have their implementation and execution time costs reduced compared to the state of the art.

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ARM processors are leaders in embedded systems, delivering high-performance computing, power efficiency, and reduced cost. For this reason, there is a relevant interest for its use in the aerospace industry. However, the use of sub-micron technologies has increased the sensitivity to radiation-induced transient faults. Thus, the mitigation of soft errors has become a major concern. Software-Implemented Hardware Fault Tolerance (SIHFT) techniques are a low-cost way to protect processors against soft errors. On the other hand, they cause high overheads in the execution time and memory, which consequently increase the energy consumption. In this work, we implement a set of software techniques based on different redundancy and checking rules. Furthermore, a low-overhead technique to protect the program execution flow is included. Tests are performed using the ARM Cortex-A9 processor. Simulated fault injection campaigns and radiation test with heavy ions have been performed. Results evaluate the trade-offs among fault detection, execution time, and memory footprint. They show significant improvements of the overheads when compared to previously reported techniques.

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