I am benchmarking my coarse-grained MD simulations with 30k beads. I noticed that MPI-GPU based mdruns used less memory and did not change much as I increased the number of nodes. Where as for MPI-OpenMP based mdruns showed increased memory usage with number of nodes.

Nodes MPI-OpenMP(GB) MPI-GPU (GB)

1 0.694 1.19

2 1.45 1.27

4 2.34 1.27

5 3.15 1.27

6 3.86 1.28

8 4.86 1.25

9 5.5 1.25

10 5.92 1.24

For all the benchmarks I have used 3 CPUs per task and 8 Tasks per node. For MPI-GPU simulations, 4 GPUs were used. I am trying to understand why MPI-GPU based mdruns are so memory efficient.

Thank you in advanced.