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Accurate Estimation of Program Error Rate for Timing-Speculative Processors

机译:时序推测处理器的程序错误率的准确估计

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We propose a framework that estimates the error rate experienced by an application as it runs on a timing-speculative processor. The framework uses an instruction error model that is comparable in accuracy to low-level simulations—as it considers the effects of operand values, preceding instructions, datapath configuration, and error correction scheme, as well as process variation, including its spatial correlation property—and yet efficient enough to allow its application in Monte Carlo experiments to characterize large program input datasets. We then use statistical limit theorems to estimate program error rate and quantify the effect of inter-instruction correlations.
机译:我们提出了一个框架,用于估计应用程序在定时推测处理器上运行时所经历的错误率。该框架使用的指令错误模型的精度可与低级仿真相媲美,因为该模型考虑了操作数值,先前指令,数据路径配置和纠错方案以及过程变化(包括其空间相关性)的影响,而且效率足够高,可以在蒙特卡洛实验中应用,以表征大型程序输入数据集。然后,我们使用统计极限定理来估计程序错误率并量化指令间关联的影响。

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