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A fast and accurate hybrid fault injection platform for transient and permanent faults

机译:用于瞬态和永久性故障的快速准确的混合故障注入平台

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摘要

Many ground-level and space systems require reliability testing before their deployment, since they are increasingly susceptible to transient and permanent faults. Such process must be accurate, controllable, generic, cheap, and fast. Even though fault injection at gate-level is often the most appropriate solution when one seeks for accuracy and controllability, it is very time-consuming. Considering that, this work proposes a hybrid fault injection framework that automatically switches between RTL and gate-level simulation modes. By using a complex 8-issue VLIW processor as case-study, we show that the injection process can be accelerated by more than 10x for transient faults and almost 2 times for permanent faults over conventional injectors, while maintaining gate-level accuracy and controllability. The proposed framework is generic, so that faults can be injected into any arbitrary circuit, which is demonstrated by also injecting faults in a neural network and achieving a speedup of more than 30x.
机译:许多地面和空间系统需要在部署之前需要可靠性测试,因为它们越来越容易受到瞬态和永久性故障的影响。此类过程必须准确,可控,通用,便宜,快速。尽管在门级的故障注入通常是最合适的解决方案,但在寻求准确性和可控性时,它也非常耗时。考虑到这一点,这项工作提出了一种混合故障注入框架,可在RTL和门级仿真模式之间自动切换。通过使用复杂的8篇VLIW处理器作为案例研究,我们表明注入过程可以加速超过10倍的瞬态故障,并且在传统喷射器上永久性故障几乎2次,同时保持栅极级精度和可控性。所提出的框架是通用的,因此可以将故障注入任何任意电路,这也通过在神经网络中注入故障并实现超过30倍的加速来说明。

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