While GROMACS is accessible, open-source, and has guardrails to ensure a simulation remains physically reasonable, there are hardware considerations one must take into account during installation and setup. GROMACS is now conda-installable, but manual installation and setup may require careful curation of shared libarries, particularly on HPC resources. During manual installation, one must ensure the requisite libraries (such as CUDA) are setup prior. GROMACS must also be compiled separately from any standard library, which maximizes installation flexibility but can be daunting for newer users. Critically, since GROMACS simulations often balance between both CPU and GPU, it is important to choose hardware with similar GPU and CPU speeds to minimize waiting time. If one of the two components is much faster than the other, there will be an inefficient waiting period where one component is sitting idle waiting for its counterpart to finish, a term referred to as "load imbalance". It is worth noting however that modern GROMACS versions are also capable of running GPU resident simulations.