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Title: Time-sliced quantum circuit partitioning for modular architectures
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.
Authors:
; ; ;
Award ID(s):
1730449
Publication Date:
NSF-PAR ID:
10191179
Journal Name:
CF '20: Proceedings of the 17th ACM International Conference on Computing Frontiers
Page Range or eLocation-ID:
98 to 107
Sponsoring Org:
National Science Foundation
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