Multi-core quantum architectures offer a solution to the scalability limitations of traditional monolithic designs. However, dividing the system into multiple chips introduces a critical bottleneck: communication between cores. This paper introduces qcomm, a simulation tool designed to assess the impact of communication on the performance of scalable multi-core quantum architectures. Qcomm allows users to adjust various architectural and physical parameters of the system, and outputs various communication metrics. We use qcomm to perform a preliminary study on how these parameters affect communication performance in a multi-core quantum system.
Multi-core quantum architectures offer a solution to the scalability limitations of traditional monolithic designs. However, dividing the system into multiple chips introduces a critical bottleneck: communication between cores. This paper introduces qcomm, a simulation tool designed to assess the impact of communication on the performance of scalable multi-core quantum architectures. Qcomm allows users to adjust various architectural and physical parameters of the system, and outputs various communication metrics. We use qcomm to perform a preliminary study on how these parameters affect communication performance in a multi-core quantum system.
The scalability of quantum computing is constrained by the physical and architectural limitations of monolithic quantum processors. Modular multi-core quantum architectures, which interconnect multiple quantum cores (QCs) via classical and quantum-coherent links, offer a promising alternative to address these challenges. However, transitioning to a modular architecture introduces communication overhead, where classical communication plays a crucial role in executing quantum algorithms by transmitting measurement outcomes and synchronizing operations across QCs. Understanding the impact of classical communication on execution time is therefore essential for optimizing system performance. In this work, we introduce qcomm , an open-source simulator designed to evaluate the role of classical communication in modular quantum computing architectures. qcomm provides a high-level execution and timing model that captures the interplay between quantum gate execution, entanglement distribution, teleportation protocols, and classical communication latency. We conduct an extensive experimental analysis to quantify the impact of classical communication bandwidth, interconnect types, and quantum circuit mapping strategies on overall execution time. Furthermore, we assess classical communication overhead when executing real quantum benchmarks mapped onto a cryogenically-controlled multi-core quantum system. Our results show that, while classical communication is generally not the dominant contributor to execution time, its impact becomes increasingly relevant in optimized scenarios—such as improved quantum technology, large-scale interconnects, or communication-aware circuit mappings. These findings provide useful insights for the design of scalable modular quantum architectures and highlight the importance of evaluating classical communication as a performance-limiting factor in future systems.
Modular architectures are a promising approach to scaling quantum computers beyond the limits of monolithic designs. However, non-local communications between different quantum processors might significantly impact overall system performance. In this work, we investigate the role of the network infrastructure in modular quantum computing architectures, focusing on coherence loss due to communication constraints. We analyze the impact of classical network latency on quantum teleportation and identify conditions under which it becomes a bottleneck. Additionally, we study different network topologies and assess how communication resources affect the number and parallelization of inter-core communications. Finally, we conduct a full-stack evaluation of the architecture under varying communication parameters, demonstrating how these factors influence the overall system performance. The results show that classical communication does not become a bottleneck for systems exceeding one million qubits, given current technology assumptions, even with modest clock frequencies and parallel wired interconnects. Additionally, increasing quantum communication resources generally shortens execution time, although it may introduce additional communication overhead. The optimal number of quantum links between QCores depends on both the algorithm being executed and the chosen inter-core topology. Our findings offer valuable guidance for designing modular architectures, enabling scalable quantum computing.
Modular quantum processor architectures are envisioned as a promising solution for the scalability of quantum computing systems beyond the Noisy Intermediate Scale Quantum (NISQ) era. Based upon interconnecting tens to hundreds of quantum processors (i.e cores) via quantum coherent and classical links, this approach unravels the pressing limitations of densely qubit-packed monolithic processors, mainly by mitigating the requirements of qubit control and enhancing qubit isolation. Therefore, this new architectural design enables executing large-scale algorithms in a distributed manner. In order to assess the performance and optimize such architectures, it is crucial to analyze the quantum state transfers occurring via inter-core communication networks, referred to as inter-core qubit traffic. This would provide insights to improve the software and hardware stack for multi-core quantum computers. To this aim, we present a characterization of the spatio-temporal inter-core qubit traffic for different large-scale quantum algorithms. The programs are compiled on an all-to-all connected multi-core architecture that supports up to around 1000 qubits. We characterize the qubit traffic based on multiple performance metrics to assess the computational process and the communication overhead. Based on the showcased results, we conclude on the parallelization and scalability of presented algorithms, qualitatively evaluate the resource requirements as we scale circuit sizes, and lay the foundations of application-oriented benchmarking of large-scale multi-core architectures.
Multi-core quantum computing has been identified as a solution to the scalability problem of quantum computing. However, interconnecting quantum chips is not trivial, as quantum communications have their share of quantum weirdness: quantum decoherence and the no-cloning theorem makes transferring qubits a harsh challenge, where every extra nanosecond counts and retransmission is simply impossible. In this paper, we present our first steps towards thorough modeling of quantum communications for multi-core quantum computers, which may be considered as a middle point between the well-known paradigms of Quantum Internet and Network-on-Chip. In particular, we stress the deep entanglement that exists between latency and error rates in quantum computing, and how this affects the quantum network design for this scenario. Moreover, we show the concomitant trade-off between computation and communication resources for a set of parameters out of state-of-the-art experimental research. The observed behavior lets us foresee the potential of multi-core quantum architectures.
Being a very promising technology, with impressive advances in the recent years, it is still unclear how quantum computing will scale to satisfy the requirements of its most powerful applications. Although continued progress in the fabrication and control of qubits is required, quantum computing scalability will depend as well on a comprehensive architectural design considering a multi-core approach as an alternative to the traditional monolithic version, hence including a communications perspective. However, this goes beyond introducing mere interconnects. Rather, it implies consolidating the full communications stack in the quantum computer architecture. In this paper, we propose a double full-stack architecture encompassing quantum computation and quantum communications, which we use to address the monolithic versus multi-core question with a structured design methodology. For that, we revisit the different quantum computing layers to capture and model their essence by highlighting the open design variables and performance metrics. Using behavioral models and actual measurements from existing quantum computers, the results of simulations suggest that multi-core architectures may effectively unleash the full quantum computer potential.
Current monolithic quantum computer architectures have limited scalability. One promising approach for scaling them up is to use a modular or multi-core architecture, in which different quantum processors (cores) are connected via quantum and classical links. This new architectural design poses new challenges such as the expensive inter-core communication. To reduce these movements when executing a quantum algorithm, an efficient mapping technique is required. In this paper, a detailed critical discussion of the quantum circuit mapping problem for multi-core quantum computing architectures is provided. In addition, we further explore the performance of a mapping method, which is formulated as a partitioning over time graph problem, by performing an architectural scalability analysis.