微处理器中含噪热传感器位置分布优化方法

高性能处理器普遍集成热传感器，采用动态热管理技术对芯片实施连续热监控。然而，由于实际芯片中的模拟或者数字热传感器不可避免伴随噪声，使动态热管理的可靠性受到很大影响。因此，为了提高热监控的精确性，本文运用主成分分析（PCA）技术对原始热图像样本矩阵进行降维近似处理，并结合矩阵扰动分析提出基于模拟退火算法的热传感器位置分布优化方法。实验结果表明：该方法比现有的贪婪算法在热重构误差、信噪比（SNR）和误警率等性能方面有了一定提高，能够有效运用在动态热管理中实现精确的热监控。

Optimization method of thermal sensor placement for microprocessor with noise

High-performance processors employ dynamic thermal management (DTM) techniques,which use a set of on-chip thermal sensors to continuously monitor temperatures during the runtime. However, on-chip sensors are inevitably accompanied by a range of noise sources due to fabrication randomness and fluctuations, which greatly affects the reliability of DTM. Therefore, in order to improve the accuracy of thermal monitoring, this paper utilizes principal component analysis (PCA) to approximately reduce dimensionality of the original sample matrix of the thermal image, and combines it with matrix perturbation analysis to propose the optimization method of thermal sensor placement which is based on simulated annealing algorithm. Experimental results indicate that the proposed method significantly outperforms the existing greedy algorithm in the aspects of thermal reconstruction error, Signal to noise ratio (SNR) and false alarm, which can be better applied in dynamic thermal management techniques to achieve accurate thermal monitoring.