  ParSplice D. Perez, E. D. Cubuk, A. Waterland, E. Kaxiras, and A. F. Voter,
Long-Time Dynamics through Parallel Trajectory Splicing, Journal of Chemical
Theory and Computation, 2016 is a molecular dynamics method for
parallel-in-time trajectory generation, allowing this workhorse of in silico
science to strong scale on massively parallel computers. Trajectories generated
by ParSplice always have robust theoretical guarantees on their validity, with
parameter choices only affecting the parallel efficiency. This commentary
summarizes the ParSplice approach with minimal mathematical development,
emphasizing how the theoretical underpinning is essential for deployment at the
exascale.
