QNPU: Quantum Network Processor Unit for Quantum Supercomputers
- URL: http://arxiv.org/abs/2509.02827v2
- Date: Thu, 23 Oct 2025 02:28:17 GMT
- Title: QNPU: Quantum Network Processor Unit for Quantum Supercomputers
- Authors: Peiyi Li, Chenxu Liu, Ji Liu, Huiyang Zhou, Ang Li,
- Abstract summary: We propose the Quantum Network Processing Unit (QNPU), which enables quantum applications to efficiently scale beyond the capacity of individual quantum processors.<n>We show that the QNPU significantly improves the efficiency of communication between quantum nodes, paving the way for quantum supercomputing.
- Score: 12.151738673876858
- License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
- Abstract: As quantum computing progresses, the need for scalable solutions to address large-scale computational problems has become critical. Quantum supercomputers are the next upcoming frontier by enabling multiple quantum processors to collaborate effectively to solve large-scale computational problems. The emergence of quantum supercomputers necessitates an efficient interface to manage the quantum communication protocols between quantum processors. In this paper, we propose the Quantum Network Processing Unit (QNPU), which enables quantum applications to efficiently scale beyond the capacity of individual quantum processors, serving as a critical building block for future quantum supercomputers. The QNPU works alongside the Quantum Processing Unit (QPU) in our decoupled processing units architecture, where the QPU handles local quantum operations while the QNPU manages quantum communication between nodes. We design a comprehensive instruction set architecture (ISA) for the QNPU with high-level communication protocol abstractions, implemented via micro-operations that manage EPR resources, quantum operations, and classical communication. To facilitate programming, we introduce DistQASM, which extends OpenQASM with distributed quantum operations. We then propose a microarchitecture featuring both scalar and superscalar QNPU designs to enhance performance for communication-intensive quantum workloads. Finally, we evaluate the performance of our proposed QNPU design with distributed quantum workloads and demonstrate that the QNPU significantly improves the efficiency of communication between quantum nodes, paving the way for quantum supercomputing.
Related papers
- A Framework for Quantum Data Center Emulation Using Digital Quantum Computers [4.4249067508724815]
We propose a framework that emulates a distributed quantum computing system using a single quantum processor.<n>We introduce an experimentally grounded noise model based on quantum collision dynamics to quantify the interconnect-induced noise.<n>The framework is validated using IBM's quantum hardware, demonstrating the successful execution of remote gates.
arXiv Detail & Related papers (2025-09-04T09:04:54Z) - A Quantum-Classical Collaborative Training Architecture Based on Quantum
State Fidelity [50.387179833629254]
We introduce a collaborative classical-quantum architecture called co-TenQu.
Co-TenQu enhances a classical deep neural network by up to 41.72% in a fair setting.
It outperforms other quantum-based methods by up to 1.9 times and achieves similar accuracy while utilizing 70.59% fewer qubits.
arXiv Detail & Related papers (2024-02-23T14:09:41Z) - A Modular Quantum Compilation Framework for Distributed Quantum
Computing [0.0]
Distributed Quantum Computing is a scalable approach for increasing the number of available qubits for computational tasks.
We present a modular quantum compilation framework for DQC that takes into account both network and device constraints.
We also devised a strategy for remote scheduling that can exploit both TeleGate and TeleData operations.
arXiv Detail & Related papers (2023-05-04T16:13:23Z) - Oblivious Quantum Computation and Delegated Multiparty Quantum
Computation [61.12008553173672]
We propose a new concept, oblivious computation quantum computation, where secrecy of the input qubits and the program to identify the quantum gates are required.
Exploiting quantum teleportation, we propose a two-server protocol for this task.
Also, we discuss delegated multiparty quantum computation, in which, several users ask multiparty quantum computation to server(s) only using classical communications.
arXiv Detail & Related papers (2022-11-02T09:01:33Z) - Optimal Stochastic Resource Allocation for Distributed Quantum Computing [50.809738453571015]
We propose a resource allocation scheme for distributed quantum computing (DQC) based on programming to minimize the total deployment cost for quantum resources.
The evaluation demonstrates the effectiveness and ability of the proposed scheme to balance the utilization of quantum computers and on-demand quantum computers.
arXiv Detail & Related papers (2022-09-16T02:37:32Z) - The Future of Quantum Computing with Superconducting Qubits [2.6668731290542222]
We see a branching point in computing paradigms with the emergence of quantum processing units (QPUs)
Extracting the full potential of computation and realizing quantum algorithms with a super-polynomial speedup will most likely require major advances in quantum error correction technology.
Long term, we see hardware that exploits qubit connectivity in higher than 2D topologies to realize more efficient quantum error correcting codes.
arXiv Detail & Related papers (2022-09-14T18:00:03Z) - Cutting Quantum Circuits to Run on Quantum and Classical Platforms [25.18520278107402]
CutQC is a scalable hybrid computing approach that distributes a large quantum circuit onto quantum (QPU) and classical platforms ( CPU or GPU) for co-processing.
It achieves much higher quantum circuit evaluation fidelity than the large NISQ devices achieve in real-system runs.
arXiv Detail & Related papers (2022-05-12T02:09:38Z) - Summary: Chicago Quantum Exchange (CQE) Pulse-level Quantum Control
Workshop [4.279232730307778]
Quantum information processing holds great promise for pushing beyond the current frontiers in computing.
We must not only place emphasis on manufacturing better qubits, advancing our algorithms, and developing quantum software.
To scale devices to the fault tolerant regime, we must refine device-level quantum control.
arXiv Detail & Related papers (2022-02-28T08:18:59Z) - On exploring the potential of quantum auto-encoder for learning quantum systems [60.909817434753315]
We devise three effective QAE-based learning protocols to address three classically computational hard learning problems.
Our work sheds new light on developing advanced quantum learning algorithms to accomplish hard quantum physics and quantum information processing tasks.
arXiv Detail & Related papers (2021-06-29T14:01:40Z) - Quantum Federated Learning with Quantum Data [87.49715898878858]
Quantum machine learning (QML) has emerged as a promising field that leans on the developments in quantum computing to explore large complex machine learning problems.
This paper proposes the first fully quantum federated learning framework that can operate over quantum data and, thus, share the learning of quantum circuit parameters in a decentralized manner.
arXiv Detail & Related papers (2021-05-30T12:19:27Z) - Distributed Quantum Computing with QMPI [11.71212583708166]
We introduce an extension of the Message Passing Interface (MPI) to enable high-performance implementations of distributed quantum algorithms.
In addition to a prototype implementation of quantum MPI, we present a performance model for distributed quantum computing, SENDQ.
arXiv Detail & Related papers (2021-05-03T18:30:43Z) - Quantum circuit architecture search for variational quantum algorithms [88.71725630554758]
We propose a resource and runtime efficient scheme termed quantum architecture search (QAS)
QAS automatically seeks a near-optimal ansatz to balance benefits and side-effects brought by adding more noisy quantum gates.
We implement QAS on both the numerical simulator and real quantum hardware, via the IBM cloud, to accomplish data classification and quantum chemistry tasks.
arXiv Detail & Related papers (2020-10-20T12:06:27Z)
This list is automatically generated from the titles and abstracts of the papers in this site.
This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.