Performance comparisons between the V100 and MI100 runs lead to following observations. In the smallest example, V100 runs are 1-2.3x faster with respect to MI100 runs. However, as the system size gets bigger, the performances become similar. The reasons for this behaviour include the use of different linear solvers for matrix diagonalization and differences in hardware platforms. To understand the performance of GPU kernels better, we report kernel run times of all the important device kernels on the V100 and MI100. Note V100 GPU has a peak FP64 capability up to 7.8 TFLOPS, 0.9 TB/s global memory bandwidth whereas for the MI100, these are 11.5 TFLOPS and 1.2 TB/s respectively. Both types of hardware allows a maximum of 255 registers per thread, and currently, this limits the performance of most of our kernels. Interestingly, the kernels compiled for V100 utilize a lower number of registers per thread in comparison to the MI100. This is most likely due to the maturity of the CUDA compiler.