GPUs have been widely used in current high-performance computing systems. However, their performance is severely constrained by the different directions of control flow during runtime. In response to this problem, warp regrouping methods are generally applied to combine the threads that execute the same branch path within one or more warps, thus obtaining a new warp. However, some unnecessary reorganization existing in these methods introduces additional performance overheads. We analyze the sources of regrouping overhead and propose a partial warp regrouping approach. Under the premise of ensuring certain efficiency, it reduces the reorganization of warps with a large number of active threads so as to avoid performance overhead. Experimental results indicate that the proposed method can significantly reduce unnecessary overheads while ensuring regrouping efficiency.