Error injection-based study of soft error propagation in AMD Bulldozer microprocessor module

C. Constantinescu, Mike Butler, Chris Weller
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引用次数: 9

Abstract

Single-event upsets (SEU) and single-event transients (SET) may lead to crashes or even silent data corruption (SDC) in microprocessors. Error detection and recovery features are employed to mitigate the impact of SEU and SET. However, these features add performance, area, power, and cost overheads. As a result, designers must concentrate their efforts on protecting the most sensitive areas of the processor. Simulated error injection was used to study the propagation of the SEU-induced soft errors in the latest AMD microprocessor module, Bulldozer. This paper presents the Bulldozer architecture, error injection methodology, and experimental results. Propagation of soft errors is quantified by derating factors. Error injection is performed both at the module and unit level, derating factors and simulation times being compared. Accuracy is assessed by deriving confidence intervals of the derating factors. The experiments point out the most sensitive units of the Bulldozer module, and allow efficient implementation of the error-handling features.
基于误差注入的AMD推土机微处理器模块软误差传播研究
单事件中断(SEU)和单事件瞬变(SET)可能导致微处理器崩溃甚至静默数据损坏(SDC)。采用错误检测和恢复功能来减轻SEU和SET的影响。然而,这些特性增加了性能、面积、功耗和成本开销。因此,设计人员必须集中精力保护处理器最敏感的区域。采用模拟错误注入的方法,研究了由seu引起的软错误在AMD最新微处理器模块Bulldozer中的传播。本文介绍了推土机的结构、错误注入方法和实验结果。软误差的传播通过降额因子进行量化。错误注入在模块和单元级别执行,降额因子和仿真时间进行比较。通过推导降额因子的置信区间来评估准确性。实验指出了推土机模块中最敏感的单元,并允许有效地实现错误处理功能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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