A System Architecture for Low Latency Multiprogramming Quantum Computing

TL;DR

This paper introduces FLAMENCO, a system that enables low-latency, high-fidelity multiprogramming in quantum computing by using offline compilation and a streamlined runtime orchestrator, overcoming online compilation bottlenecks.

Contribution

FLAMENCO's architecture allows independent offline compilation and dynamic region selection, significantly reducing runtime latency and improving fidelity in multiprogramming quantum workloads.

Findings

Achieves over 5× runtime speedup compared to state-of-the-art baselines.

Removes online compilation overhead for quantum multiprogramming.

Maintains high device utilization and fidelity as concurrency increases.

Abstract

As quantum systems scale, Multiprogramming Quantum Computing (MPQC) becomes essential to improve device utilization and throughput. However, current MPQC pipelines rely on expensive online compilation to co-optimize concurrently running programs, because quantum executables are device-dependent, non-portable across qubit regions, and highly susceptible to noise and crosstalk. This online step dominates runtime and impedes low-latency deployments for practical, real-world workloads in the future, such as repeatedly invoked Quantum Neural Network (QNN) services. We present FLAMENCO, a fidelity-aware multi-version compilation system that enables independent offline compilation and low-latency, high-fidelity multiprogramming at runtime. At the architecture level, FLAMENCO abstracts devices into compute units to drastically shrink the search space of region allocation. At compile time, it generates diverse executable versions for each program -- each bound to a distinct qubit region -- allowing dynamic region selection at runtime and overcoming non-portability. At runtime, FLAMENCO employs a streamlined orchestrator that leverages post-compilation fidelity metrics to avoid conflicts and mitigate crosstalk, achieving reliable co-execution without online co-optimization. Comprehensive evaluations against state-of-the-art MPQC baselines show that FLAMENCO removes online compilation overhead, achieves over 5$\times$ runtime speedup, improves execution fidelity, and maintains high utilization as concurrency increases.