Current quantum computer designs will not scale. To scale beyond small
prototypes, quantum architectures will likely adopt a modular approach with
clusters of tightly connected quantum bits and sparser connections between
clusters. We exploit this clustering and the statically-known control flow of
quantum programs to create tractable partitioning heuristics which map quantum
circuits to modular physical machines one time slice at a time. Specifically,
we create optimized mappings for each time slice, accounting for the cost to
move data from the previous time slice and using a tunable lookahead scheme to
reduce the cost to move to future time slices. We compare our approach to a
traditional statically-mapped, owner-computes model. Our results show strict
improvement over the static mapping baseline. We reduce the non-local
communication overhead by 89.8\% in the best case and by 60.9\% on average. Our
techniques, unlike many exact solver methods, are computationally tractable.Comment: Appears in CF'20: ACM International Conference on Computing Frontier