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Pattern based runtime voltage emergency prediction: An instruction-aware block sparse compressed sensing approach

机译:基于模式的运行时电压紧急预测:指令感知块稀疏压缩感知方法

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The relentless technology scaling calls for reduced supply voltage for dynamic power suppression. On the other hand, transistor threshold voltage cannot be scaled at the same pace to avoid excessive leakage power. Consequently, the noise margin is significantly reduced, leading to the deployment of various noise management systems that handle runtime voltage emergencies. Most of these systems rely on on-chip noise sensors, which are large in size and consume significant power. To tackle this issue, in this paper we propose a sensor-less voltage emergency estimation framework. It explores the relationship between switching activities and noise, and takes advantage of block sparse compressed sensing developed by the signal processing society. Experimental results on a few industrial designs show that by monitoring registers, voltage emergencies can be successfully predicted.
机译:无情的技术扩展要求降低电源电压以实现动态功率抑制。另一方面,晶体管阈值电压不能以相同的速度缩放,以避免过多的泄漏功率。因此,噪声余量被大大降低,从而导致部署了各种噪声管理系统来应对运行时的紧急情况。这些系统中的大多数都依赖于片上噪声传感器,该传感器尺寸较大且消耗大量功率。为了解决这个问题,在本文中我们提出了一种无传感器的电压紧急估计框架。它探讨了开关活动与噪声之间的关系,并利用了信号处理协会开发的块稀疏压缩感知技术。在一些工业设计上的实验结果表明,通过监视寄存器,可以成功预测电压紧急情况。

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