Software-Hardware Co-Optimization for Computational Chemistry on Superconducting Quantum Processors
Computational chemistry is the leading application to demonstrate the advantage of quantum computing in the near term. However, large-scale simulation of chemical systems on quantum computers is currently hindered due to a mismatch between the computational resource needs of the program and those av...
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Main Authors | , , |
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Format | Journal Article |
Language | English |
Published |
14.05.2021
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Subjects | |
Online Access | Get full text |
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Summary: | Computational chemistry is the leading application to demonstrate the
advantage of quantum computing in the near term. However, large-scale
simulation of chemical systems on quantum computers is currently hindered due
to a mismatch between the computational resource needs of the program and those
available in today's technology. In this paper we argue that significant new
optimizations can be discovered by co-designing the application, compiler, and
hardware. We show that multiple optimization objectives can be coordinated
through the key abstraction layer of Pauli strings, which are the basic
building blocks of computational chemistry programs. In particular, we leverage
Pauli strings to identify critical program components that can be used to
compress program size with minimal loss of accuracy. We also leverage the
structure of Pauli string simulation circuits to tailor a novel hardware
architecture and compiler, leading to significant execution overhead reduction
by up to 99%. While exploiting the high-level domain knowledge reveals
significant optimization opportunities, our hardware/software framework is not
tied to a particular program instance and can accommodate the full family of
computational chemistry problems with such structure. We believe the co-design
lessons of this study can be extended to other domains and hardware
technologies to hasten the onset of quantum advantage. |
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DOI: | 10.48550/arxiv.2105.07127 |