As power density increases exponentially, run-time regulation of operating temperature by dynamic thermal management becomes imperative. This paper proposes a novel approach to real-time thermal estimation at chip level for efficient dynamic thermal management in lieu of the thermal sensors, which are erroneous and having longer delays. Our new approach is based on the observation that the average power consumption of architecture level modules in microprocessors running typical workloads determines the trend of temperature variations. Such a feature can be exploited by applying fast moment matching technique in frequency domain. To obtain the transient temperature changes due to initial condition and constant power input pattern, numerically stable moment matching approach is carried out to speed up on-line temperature tracking with high accuracy and low overhead. The resulting fast thermal analysis algorithm has linear time complexity in run-time setting and leads to about two orders of magnitude speed-up over traditional integrationbased transient analysis. The average maximum error under running typical benchmarks is only about 0.37 degree C as compared to other wellaccepted simulation tools.