To sustain Moore's law, three-dimensional integrated circuit (3-D IC) is a promising solution to achieve high performance and low cost targets. However, its operating temperature is higher than that of a 2-D IC because of its high power density of stacked dies and ill of heat dissipation capability. Therefore, on-chip thermal effects have become major concerns of 3-D ICs. Utilizing look-up table approach, this paper, LUTSim, provides two thermal simulation engines, I-LUTSim and S-LUTSim, to efficiently calculate the thermal profile of a 3-D IC. I-LUTSim is suitable for full-chip thermal analysis, and S-LUTSim is suited for incremental-thermal updating. With utilizing the prebuilt tables, compared with a commercial tool ANSYS, the absolute error of I-LUTSim is less than 0.29%. Moreover, with negligible loss of accuracy, I-LUTSim can be 38.8 times faster than a well-known matrix solver SuperLU for performing full-chip thermal simulation. Besides, S-LUTSim can be over 1.05 million times faster than SuperLU for adjusting the thermal profile after inserting/removing a through silicon via.

This work presents an iterative look-up table based thermal simulator, I-LUTSim, to efficiently estimate the temperature profile of three-dimensional integrated circuits. I-LUTSim includes two stages. First, the pre-process stage constructs thermal impulse response tables. Then, the simulation stage iteratively calculates the temperature profile via the table lookup. With this two-stage scheme, the maximum absolute error of I-LUTSim is less than 0.41% compared with that of a commercial tool ANSYS. Moreover, I-LUTSim is at least an order of magnitude faster than a fast matrix solver SuperLU [1] for the full-chip temperature simulation.

By combining analytical and numerical simulation techniques, this work develops a hybrid thermal simulator, NUMANA, which can effectively deal with complicated material structures, to estimate the temperature profile of a 3-D IC. Compared with a commercial tool, ANSYS, its maximum relative error is only 1.84%. Compared with a well known linear system solver, SuperLU [1], it can achieve orders of magnitude speedup.