Acoustic-sensor-based soft error resilience is particularly promising, since it can verify the absence of soft errors and eliminate silent data corruptions at a low hardware cost. However, the state-of-the-art work incurs a significant performance overhead for in-order cores due to frequent structural/data hazards during the verification. To address the problem, this paper presents Turnpike, a compiler/architecture co-design scheme that can achieve lightweight yet guaranteed soft error resilience for in-order cores. The key idea is that many of the data computed in the core can bypass the soft error verification without compromising the resilience. Along with simple microarchitectural support for realizing the idea, Turnpike leverages compiler optimizations to further reduce the performance overhead. Experimental results with 36 benchmarks demonstrate that Turnpike only incurs a 0-14% run-time overhead on average while the state-of-the-art incurs a 29-84% overhead when the worst-case latency of the sensor based error detection is 10-50 cycles.
翻译:以声波传感器为基础的软错误抗御能力特别有希望,因为它可以以较低的硬件成本核查软错误的缺失,并消除无声数据腐败。然而,由于在核查过程中经常出现结构性/数据性危害,最先进的工作对定序核心产生了巨大的性能管理管理费用。为了解决这个问题,本文展示了编译/建筑设计共同设计方案Turnpike, 这是一个编译者/建筑设计共同设计方案,它能够使定序核心实现轻量但有保障的软错误抗御能力。关键的想法是,在核心中计算的许多数据可以绕过软错误核查,而不会损害复原力。与简单的微观构造支持一起,Turnpike利用编译器优化来进一步减少性能管理费用。36个基准的实验结果表明,在传感器最差的误差探测周期为10-50周期时,Turnpike只产生0.14%的运行时间管理费用。