  The interplay of quantum and classical simulation and the delicate divide
between them is in the focus of massively parallelized tensor network state
(TNS) algorithms designed for high performance computing (HPC). In this
contribution, we present novel algorithmic solutions together with
implementation details to extend current limits of TNS algorithms on HPC
infrastructure building on state-of-the-art hardware and software technologies.
Benchmark results obtained via large-scale density matrix renormalization group
(DMRG) simulations are presented for selected strongly correlated molecular
systems addressing problems on Hilbert space dimensions up to
$2.88\times10^{36}$.
