The weakly connected components of the time-evolving graph have been widely used in many areas, such as traffic network construction, information push of recommendation systems, etc. However, most methods for the weakly connected components ignore the impact of the non-uniform memory access (NUMA) architecture, that is, the high remote memory access delay leads to low execution efficiency. This study proposes a NUMA-based delayed sending method to find the weakly connected components of the time-evolving graph. It minimises the number of remote accesses and improves computational efficiency through reasonable data memory layout and controlling the number of exchanges between NUMA nodes. The experimental results show that the performance of the NUMA-based delayed sending method is better than the methods provided by the current popular graph processing systems Ligra and Polymer.