  The presence of many degenerate $d/f$ orbitals makes polynuclear transition
metal compounds such as iron-sulfur clusters in nitrogenase challenging for
state-of-the-art quantum chemistry methods. To address this challenge, we
present the first distributed multi-GPU (Graphics Processing Unit) \emph{ab
initio} density matrix renormalization (DMRG) algorithm, suitable for modern
high-performance computing (HPC) infrastructures. The central idea is to
parallelize the most computationally intensive part - the multiplication of
$O(K^2)$ operators with a trial wavefunction, where $K$ is the number of
spatial orbitals, by combining operator parallelism for distributing the
workload with a batched algorithm for performing contractions on GPU. With this
new implementation, we are able to reach an unprecedentedly large bond
dimension $D=14000$ on 48 GPUs (NVIDIA A100 80 GB SXM) for an active space
model (114 electrons in 73 active orbitals) of the P-cluster, which is nearly
three times larger than the bond dimensions reported in previous DMRG
calculations for the same system using only CPUs.
