An Evaluation of Soft Processors as a Reliable Computing Platform

An Evaluation of Soft Processors as a Reliable Computing Platform Michael Robert Gardiner Department of Electrical and Computer Engineering, BYU Master of Science This study evaluates the benefits and limitations of soft processors operating in a radiation-hardened FPGA, focusing primarily on the performance and reliability of these systems. FPGAs designs for four popular soft processors, the MicroBlaze, LEON3, CortexM0 DesignStart, and OpenRISC 1200 are developed for a Virtex-5 FPGA. The performance of these soft processor designs is then compared on ten widely-used benchmark programs. Benchmarking results indicate that the MicroBlaze has the best integer performance of the soft processors, with at least 2.23X better performance on average than the other three processors. However, the LEON3 has the best floating-point performance, with benchmark scores 8.9X higher on average than its competitors. The soft processors’ performance is also compared against estimated benchmark scores for a radiation-hardened processor, the RAD750. We find the average performance of the RAD750 to be 2.58X better than the best soft processor scores on each benchmark, although the best soft processor scores were higher on two benchmarks. The soft processors’ inability to compete with the performance of the decade-old RAD750 illustrates the substantial performance gap between hard and soft processor architectures. Although soft processors are not capable of competing with rad-hard processors in performance, the flexibility they provide nevertheless makes them a desirable option for space systems where speed is not the key issue. Fault injection experiments are also completed on three of the soft processors to evaluate their configuration memory sensitivity. Our results demonstrate that the MicroBlaze is less sensitive than the LEON3 and the Cortex-M0 DesignStart, but that the LEON3 has lower sensitivity per FPGA slice than the other processors. A combined metric for soft processor performance and configuration sensitivity is then developed to aid future researchers in evaluating the trade-offs between these two distinct processor attributes.

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