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The increasing system complexity of FPGA-based hardware designs and shortening of time-to-market have motivated the adoption of new designing methodologies focused on addressing the current need for high-performance circuits. High-Level Synthesis (HLS) tools can generate Register Transfer Level (RTL) designs from high-level software programming languages. These tools have evolved significantly in recent years, providing optimized RTL designs, which can serve the needs of safety-critical applications that require both high performance and high reliability levels. However, a reliability evaluation of HLS-based designs under soft errors has not yet been presented. In this work, the trade-offs of different HLS-based designs in terms of reliability, resource utilization, and performance are investigated by analyzing their behavior under soft errors and comparing them to a standard processor-based implementation in an SRAM-based FPGA. Results obtained from fault injection campaigns and radiation experiments show that it is possible to increase the performance of a processor-based system up to 5,000 times by changing its architecture with a small impact in the cross section (increasing up to 8 times), and still increasing the Mean Workload Between Failures (MWBF) of the system. [ABSTRACT FROM PUBLISHER]

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. [ABSTRACT FROM PUBLISHER]