  The constructions of configuration interaction (CI) expansions from a
matrix-product state (MPS) involves numerous matrix operations and the skillful
sampling of important configurations when in a huge Hilbert space. In this
work, we present an efficient procedure for constructing CI expansions from MPS
using the Charm++ parallel programming framework, upon which automatic load
balancing and object migration facilities can be employed. This procedure was
employed in the MPS-to-CI utility (Moritz et al., J. Chem. Phys. 2007, 126,
224109), sampling-reconstructed complete active space algorithm (SR-CAS,
Boguslawski et al., J. Chem. Phys. 2011, 134, 224101) and entanglement-driven
genetic algorithm (EDGA, Luo et al., J. Chem. Theory Comput. 2017, 13,
4699-4710). It enhances productivity and allows the sampling programs evolve to
their population-expansion versions (e.g., EDGA with population expansion
[PE-EDGA]). Examples of 1,2-dioxetanone and firefly dioxetanone anion (FDO-)
molecules demonstrated that 1) the procedure could be flexibly employed among
various multi-core architectures; 2) the parallel efficiencies could be
persistently improved simply by increasing the proportion of asynchronous
executions; 3) PE-EDGA could construct a CAS-type CI wave function from a huge
Hilbert space, with 0.9952 CI completeness and 96.7% correlation energy via
~1.66x10^6 configurations (only 0.0000028% of the total configurations) of a
bi-radical state of FDO- molecule using the full valence active space within a
few hours.
