Graph coloring was used to address resource competition for the two typical computing procedures, including the flux summation and the calculation of local maximum pressure. There were three optimizations applied on graph coloring including shared memory, the reordering of volume and face indices, and the reordering of face variables. The 3D aerodynamics application with a series of mesh sizes was used in the performance test by double and single precision floating point operations on GPU Nvidia Tesla V100 and K80. The performance tests show that the shared memory is not obvious in performance. Furthermore, the reorder of volume and face indices reduces the performance of graph coloring.It is found that the reorder of face variables can increase performance remarkably. Specifically, the performance of graph coloring is increased by around 20% on V100 and 15% on K80.