Optimized compiler for Distributed Quantum Computing

TL;DR

This paper presents an optimized compiler for distributed quantum computing that models resource-efficient circuit compilation using a parametric ILP approach, reducing execution time and resource usage on distributed architectures.

Contribution

It introduces a novel ILP-based optimization framework that minimizes runtime and resource consumption for distributed quantum circuit compilation, including parallelization strategies.

Findings

Effective reduction in execution time through binary search optimization.

Resource usage minimized by the ILP formulation.

Enhanced solution space via circuit manipulation and parallelization.

Abstract

Practical distributed quantum computing requires the development of efficient compilers, able to make quantum circuits compatible with some given hardware constraints. This problem is known to be tough, even for local computing. Here, we address it on distributed architectures. As generally assumed in this scenario, telegates represent the fundamental remote (inter-processor) operations. Each telegate consists of several tasks: i) entanglement generation and distribution, ii) local operations, and iii) classical communications. Entanglement generations and distribution is an expensive resource, as it is time-consuming and fault-prone. To mitigate its impact, we model an optimization problem that combines running-time minimization with the usage of that resource. Specifically, we provide a parametric ILP formulation, where the parameter denotes a time horizon (or time availability); the objective function count the number of used resources. To minimize the time, a binary search solves the subject ILP by iterating over the parameter. Ultimately, to enhance the solution space, we extend the formulation, by introducing a predicate that manipulates the circuit given in input and parallelizes telegates' tasks.