One-Time Compilation of Device-Level Instructions for Quantum
Subroutines
- URL: http://arxiv.org/abs/2308.10787v1
- Date: Mon, 21 Aug 2023 15:23:09 GMT
- Title: One-Time Compilation of Device-Level Instructions for Quantum
Subroutines
- Authors: Aniket S. Dalvi, Jacob Whitlow, Marissa D'Onofrio, Leon Riesebos,
Tianyi Chen, Samuel Phiri, Kenneth R. Brown and Jonathan M. Baker
- Abstract summary: We develop a device-level partial-compilation (DLPC) technique that reduces compilation overhead to nearly constant.
We execute this modified pipeline on real trapped-ion quantum computers and observe significant reductions in compilation time.
- Score: 22.730983120623574
- License: http://creativecommons.org/licenses/by/4.0/
- Abstract: A large class of problems in the current era of quantum devices involve
interfacing between the quantum and classical system. These include calibration
procedures, characterization routines, and variational algorithms. The control
in these routines iteratively switches between the classical and the quantum
computer. This results in the repeated compilation of the program that runs on
the quantum system, scaling directly with the number of circuits and
iterations. The repeated compilation results in a significant overhead
throughout the routine. In practice, the total runtime of the program
(classical compilation plus quantum execution) has an additional cost
proportional to the circuit count. At practical scales, this can dominate the
round-trip CPU-QPU time, between 5% and 80%, depending on the proportion of
quantum execution time.
To avoid repeated device-level compilation, we identify that machine code can
be parametrized corresponding to pulse/gate parameters which can be dynamically
adjusted during execution. Therefore, we develop a device-level
partial-compilation (DLPC) technique that reduces compilation overhead to
nearly constant, by using cheap remote procedure calls (RPC) from the QPU
control software to the CPU. We then demonstrate the performance speedup of
this on optimal pulse calibration, system characterization using randomized
benchmarking (RB), and variational algorithms. We execute this modified
pipeline on real trapped-ion quantum computers and observe significant
reductions in compilation time, as much as 2.7x speedup for small-scale VQE
problems.
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