High-Level Energy Estimation for Submicrometric TSV Arrays

The 3-D integration using through silicon vias (TSVs) is one of the most promising approaches to overcome the interconnect delay problem of current CMOS technologies. Nevertheless, the TSV energy consumption is not negligible due to the high capacitive coupling. This paper presents an abstract and yet accurate model to estimate the pattern-dependent energy consumption in arrays of TSVs; it is the first high-level model including the effects of the voltage-dependent metal-oxide-semiconductor (MOS) capacitances surrounding each TSV and a possible temporal misalignment between the input signals. We propose a regression method to estimate the dynamic size of the coupling capacitances as a function of the bit probabilities. Experimental results for real and synthetic data streams, a submicrometer 9-bit TSV array and a 65-nm technology show that the presented TSV energy model exhibits a maximum error of 5.53%, while the traditional high-level model shows errors of up to 79.77%. Furthermore, the new insights provided by our model reveal a possibility to easily boost the efficiency of existing low-power codes for TSV structures by over 10% without affecting the coding efficiency for the planar metal wires or the encoder complexity.