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arXiv:2207.14483 · ACM Transactions on Architecture and Code Optimization

QuCloud+: A Holistic Qubit Mapping Scheme for Single/Multi-programming on 2D/3D NISQ Quantum Computers

Lei Liu, Xinglei Dou

Published Nov 7, 2023• 37 citations
arXivHTMLPDF

Abstract

Qubit mapping for NISQ superconducting quantum computers is essential to fidelity and resource utilization. The existing qubit mapping schemes meet challenges, e.g., crosstalk, SWAP overheads, diverse device topologies, etc., leading to qubit resource underutilization and low fidelity in computing results. This article introduces QuCloud+, a new qubit mapping scheme that tackles these challenges. QuCloud+ has several new designs. (1) QuCloud+ supports single/multi-programming quantum computing on quantum chips with 2D/3D topology. (2) QuCloud+ partitions physical qubits for concurrent quantum programs with the crosstalk-aware community detection technique and further allocates qubits according to qubit degree, improving fidelity, and resource utilization. (3) QuCloud+ includes an X-SWAP mechanism that avoids SWAPs with high crosstalk errors and enables inter-program SWAPs to reduce the SWAP overheads. (4) QuCloud+ schedules concurrent quantum programs to be mapped and executed based on estimated fidelity for the best practice. Experimental results show that, compared with the existing typical multi-programming study [ 12 ], QuCloud+ achieves up to 9.03% higher fidelity and saves on the required SWAPs during mapping, reducing the number of CNOT gates inserted by 40.92%. Compared with a recent study [ 30 ] that enables post-mapping gate optimizations to further reduce gates, QuCloud+ reduces the post-mapping circuit depth by 21.91% while using a similar number of gates.

DOI
10.1145/3631525

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Qubit mapping for NISQ superconducting quantum computers is essential to fidelity and resource utilization. The existing qubit mapping schemes meet challenges, e.g., crosstalk, SWAP overheads, diverse device topologies, etc., leading to qubit resource underutilization and low fidelity in computing results. This article introduces QuCloud+, a new qubit mapping scheme that tackles these challenges. QuCloud+ has several new designs. (1) QuCloud+ supports single/multi-programming quantum computing on quantum chips with 2D/3D topology. (2) QuCloud+ partitions physical qubits for concurrent quantum programs with the crosstalk-aware community detection technique and further allocates qubits according to qubit degree, improving fidelity, and resource utilization. (3) QuCloud+ includes an X-SWAP mechanism that avoids SWAPs with high crosstalk errors and enables inter-program SWAPs to reduce the SWAP overheads. (4) QuCloud+ schedules concurrent quantum programs to be mapped and executed based on estimated fidelity for the best practice. Experimental results show that, compared with the existing typical multi-programming study [ 12 ], QuCloud+ achieves up to 9.03% higher fidelity and saves on the required SWAPs during mapping, reducing the number of CNOT gates inserted by 40.92%. Compared with a recent study [ 30 ] that enables post-mapping gate optimizations to further reduce gates, QuCloud+ reduces the post-mapping circuit depth by 21.91% while using a similar number of gates.
For a specific quantum chip, multi-programming improves overall throughput and resource utilization. Previous studies on mapping multiple programs often lead to resource under-utilization, high error rate, and low fidelity. This paper proposes QuCloud, a new approach for mapping quantum programs in the cloud environment. We have three new designs in QuCloud. (1) We leverage the community detection technique to partition physical qubits among concurrent quantum programs, avoiding the waste of robust resources. (2) We design X-SWAP scheme that enables inter-program SWAPs and prioritizes SWAPs associated with critical gates to reduce the SWAP overheads. (3) We propose a compilation task scheduler that schedules concurrent quantum programs to be compiled and executed based on estimated fidelity for the best practice. We evaluate our work on publicly available quantum computer IBMQ16 and a simulated quantum chip IBMQ50. Our work outperforms the state-of-the-art work for multi-programming on fidelity and compilation overheads by 9.7% and 11.6%, respectively.
For a specific quantum chip, multi-programming helps to improve the overall throughput and resource utilization. However, previous solutions for mapping multiple programs often lead to resource under-utilization, high error rate, and low fidelity. In this paper, we propose a new approach to map concurrent quantum programs. Our approach has three critical components. The first one is the Community Detection Assisted Partition (CDAP) algorithm, which partitions physical qubits for concurrent quantum programs by considering physical typology and the error rate, avoiding the waste of robust resources. The second one is the X-SWAP scheme that enables inter-program SWAPs and prioritizes SWAPs associated with critical gates to reduce the SWAP overheads. Finally, we propose a compilation task scheduler, which dynamically selects concurrent quantum programs to be compiled and executed together based on estimated fidelity for the best practice. We evaluate our work on publicly available quantum computer IBMQ16 and a simulated quantum chip IBMQ50. Our work outperforms the state-of-the-art work for multi-programming on fidelity and compilation overheads by 12.0% and 11.6%, respectively.
For a specific quantum chip, multi-programming helps to improve overall throughput and resource utilization. However, the previous solutions for mapping multiple programs onto a quantum chip often lead to resource under-utilization, high error rate and low fidelity. In this paper, we propose a new approach to map concurrent quantum programs. Our approach has three critical components. The first one is the Community Detection Assisted Partition (CDAP) algorithm, which partitions physical qubits for concurrent quantum programs by considering both physical typology and the error rates, avoiding the waste of robust resources. The second one is the X-SWAP scheme that enables inter-program SWAP operations to reduce the SWAP overheads. Finally, we propose a compilation task scheduling framework, which dynamically selects concurrent quantum programs to be executed based on estimated fidelity, increasing the throughput of the quantum computer. We evaluate our work on publicly available quantum computer IBMQ16 and a simulated quantum chip IBMQ20. Our work outperforms the previous solution on multi-programming in both fidelity and SWAP overheads by 12.0% and 11.1%, respectively.
NISQ devices have several physical limitations and unavoidable noisy quantum operations, and only small circuits can be executed on a quantum machine to get reliable results. This leads to the quantum hardware under-utilization issue. Here, we address this problem and improve the quantum hardware throughput by proposing a Quantum Multi-programming Compiler (QuMC) to execute multiple quantum circuits on quantum hardware simultaneously. This approach can also reduce the total runtime of circuits. We first introduce a parallelism manager to select an appropriate number of circuits to be executed at the same time. Second, we present two different qubit partitioning algorithms to allocate reliable partitions to multiple circuits – a greedy and a heuristic. Third, we use the Simultaneous Randomized Benchmarking protocol to characterize the crosstalk properties and consider them in the qubit partition process to avoid the crosstalk effect during simultaneous executions. Finally, we enhance the mapping transition algorithm to make circuits executable on hardware using a decreased number of inserted gates. We demonstrate the performance of our QuMC approach by executing circuits of different sizes on IBM quantum hardware simultaneously. We also investigate this method on VQE algorithm to reduce its overhead.
The rapid progress of physical implementation of quantum computers paved the way of realising the design of tools to help users write quantum programs for any given quantum devices. The physical constraints inherent to the current NISQ architectures prevent most quantum algorithms from being directly executed on quantum devices. To enable two-qubit gates in the algorithm, existing works focus on inserting SWAP gates to dynamically remap logical qubits to physical qubits. However, their schemes lack the consideration of the depth of generated quantum circuits. In this work, we propose a depth-aware SWAP insertion scheme for qubit mapping problem in the NISQ era.
Rapid progress in the physical implementation of quantum computers gave birth to multiple recent quantum machines implemented with superconducting technology. In these NISQ machines, each qubit is physically connected to a bounded number of neighbors. This limitation prevents most quantum programs from being directly executed on quantum devices. A compiler is required for converting a quantum program to a hardware-compliant circuit, in particular, making each two-qubit gate executable by mapping the two logical qubits to two physical qubits with a link between them. To solve this problem, existing studies focus on inserting SWAP gates to dynamically remap logical qubits to physical qubits. However, most of the schemes lack the consideration of time-optimality of generated quantum circuits, or are achieving time-optimality with certain constraints. In this work, we propose a theoretically time-optimal SWAP insertion scheme for the qubit mapping problem. Our model can also be extended to practical heuristic algorithms. We present exact analysis results by using our model for quantum programs with recurring execution patterns. We have for the first time discovered an optimal qubit mapping pattern for quantum fourier transformation (QFT) on 2D nearest neighbor architecture. We also present a scalable extension of our theoretical model that can be used to solve qubit mapping for large quantum circuits.