Process variation and temperature-aware reliability management
Process variation and temperature-aware reliability management
复制标题
过程变化和温度感知可靠性管理
DOI：
10.1109/date.2010.5457139
复制
发表时间：
2010
期刊：
影响因子：
--
通讯作者：
D. Blaauw
中科院分区：
文献类型：
--
作者：
Cheng Zhuo;D. Sylvester;D. Blaauw
在大规模技术中，氧化物分解等可靠性问题已成为关键问题。动态可靠性管理（DRM）是一种动态探索系统性能与可靠性裕度之间权衡关系的机制。然而，现有的DRM方法由于不能准确地模拟对芯片可靠性有很大影响的工艺和温度参数的时空变化而受到阻碍。此外，它们还简化了假设，即未来的工作负载与当前观察到的工作负载相同。这使得他们对突然的工作量变化和异常值非常敏感。在本文中，我们提出了一个新的工作负载感知的动态可靠性管理框架，该框架考虑了过程和温度的局部变化。可靠性估计以及预测的剩余工作负载被馈送到动态电压/频率缩放模块，以管理系统可靠性并优化处理器性能。使用快速在线分析/表查找方法，我们证明了与蒙特卡罗模拟相比，平均误差为1%，加速高达5个数量级。在类alpha处理器上的实验表明，我们的DRM框架充分利用了可用的余量，平均性能提高了28.7%。
In aggressively scaled technologies, reliability concerns such as oxide breakdown have become a key issue. Dynamic reliability management (DRM) has been proposed as a mechanism to dynamically explore the trade-off between system performance and reliability margin. However, existing DRM methods are hampered by the fact that they do not accurately model spatial and temporal variations in process and temperature parameters which have a strong impact on chip reliability. In addition, they make the simplifying assumption that the future workloads are identical to the currently observed one. This makes them sensitive to sudden workload variations and outliers. In this paper, we present a novel workload-aware dynamic reliability management framework that accounts for local variations in both the process and temperature. The reliability estimation, along with the predicted remaining workload is fed to a dynamic voltage/frequency scaling module to manage the system reliability and optimize processor performance. Using a fast on-line analytical/table-look-up method we demonstrate an average error of 1% with up to 5 orders of magnitude speedup compared to Monte Carlo simulation. Experiments on an Alpha-like processor show our DRM framework fully utilizes the available margin and achieves 28.7% performance improvement on average.