Parallelizing Program Execution on Distributed Quantum Systems via Compiler/Hardware Co-Design

TL;DR

This paper presents a hardware and compiler co-design approach to enable parallel execution of quantum algorithms on distributed quantum systems, significantly improving performance and speedup over serial execution models.

Contribution

It introduces a flexible hardware design and a compiler optimization technique that together enhance parallelism in distributed quantum computing systems.

Findings

Achieved up to 56.2x speedup on benchmark algorithms.

Hardware and compiler co-design enables consistent speedup across various algorithms.

Demonstrated the effectiveness of the approach through a runtime calculator and benchmarks.

Abstract

As quantum computers continue to improve and support larger, more complex computations, smart control hardware and compilers are needed to efficiently leverage the capabilities of these systems. This paper introduces a novel approach to enhance the execution of quantum algorithms on distributed quantum systems. The proposed method involves the development of a hardware design that supports parallel instruction execution and a compiler that modifies the order of instructions to increase parallelism opportunities. The hardware design can be flexibly configured to facilitate parallel execution of instructions that have identical parameters. Furthermore, the compiler uses the underlying hardware constraints to intelligently reorder and decompose instructions to avoid dependencies. The compiler, hardware, and their combination are evaluated using a runtime calculator and a benchmark quantum algorithm set. The results demonstrate a significant speedup, achieving a maximum average speedup of 16.5x and a maximum single-benchmark speedup of 56.2x relative to a baseline, serial execution model. Furthermore, we show a speedup can be obtained across all benchmarks using any of the proposed hardware schemes, although the degree of speedup is largely dependent on the type of quantum algorithm. Taken together, the results of this paper represent a significant step towards realizing high-performance quantum computing systems.