There is increasing demand for the high-speed processing of large-scale graphs in various fields. However, such graph processing requires irregular calculations, making it difficult to scale performance on large-scale distributed memory systems. Against this background, Graph500, a competition for evaluating the performance of large-scale graph processing, has been held. We developed breadth-first search (BFS), which is one of the benchmark kernels used in Graph500, and took the top spot a total of 10 times using the K computer. In this paper, we tune BFS performance and evaluate it using the supercomputer Fugaku, which is the successor to the K computer. The results of evaluating BFS for a large-scale graph composed of about 1.1 trillion vertices and 17.6 trillion edges using 92,160 nodes of Fugaku indicate that Fugaku has 2.27 times the performance of the K computer. Fugaku took the top spot on Graph500 in June 2020.