With the improvement of the nanometer technology

the influences among temperature

leakage power and heat conductance become increasingly significant and it should be taken into account in 3D chip comprehensive thermal analysis to solve the accurate temperature based on the iterative solution.The comprehensive thermal analysis method uses the nodal power density vector and the heat conductance matrix to solve the nodal temperature vector

and then

refreshes power density and heat conductance with the obtained nodal temperature.In order to improve the efficiency of 3D chip comprehensive thermal analysis

this work uses the heat conductance matrix as the precondition under a setting temperature.Then it proposes an efficient algorithm TPG-FTCG (CG with the Fast Transform-based Preconditioner) which has double-loop and lower inner-loop iterations.According to TPG-FTCG's fast inner-loop convergence rate

this work removes TPG-FTCG's inner-loop part then proposes a more efficient TPG solving algorithm TPG-Sli (Single-loop iterative)

which only has single-loop iterative and fewer iterations.Based on the GPU parallel computing

this work compiles and refines TPG-Sli's GPU-parallel-computing algorithm.Experimental results demonstrate that:On the premise of precision losing

the TPG-Sli's GPU algorithm can achieve about 120X speedup compared with the TPG-ICCG algorithm

which uses the classical and efficient ICCG to deal with the 3D chip comprehensive thermal analysis.