Abstract: With the increasing power density of multicore processors, the temperature-constrained performance analysis becomes a key component for the early design optimization of multicore processors. When different tasks are running, the temperatures of processors exhibit significant variation. However, most of existing researches for the steady-state analysis are based on the assumption that all tasks have the same power dissipation and distribution, and do not consider the impact of task variation on the performance of thermal-aware multicore processors. In order to improve the analysis accuracy of the steady-state throughput of multicore processors under temperature constraint, the task variation is taken into account, and a new method of maximum throughput analysis is proposed based on the HotSpot thermal model for the multicore processors which use dynamic voltage and frequency scaling (DVFS) to dynamically manage temperature. The task characteristic is incorporated into the model of performance analysis, and the relationship among the characteristics of tasks on various cores is demonstrated when the multicore processors achieve maximum throughput. And then the analysis of maximum throughput of multicore processors under temperature constraint is transformed to the problem of linear programming. Experimental results show that the proposed method achieves better accuracy of analysis, and task characteristic has the significant impact on the maximum steady-state throughput of temperature-constrained multicore processors.