Progress in the realm of quantum technologies is paving the way for a multitude of potential applications across different sectors. However, the reduced number of available quantum computers, their technical limitations and the high demand for their use are posing some problems for developers and researchers. Mainly, users trying to execute quantum circuits on these devices are usually facing long waiting times in the tasks queues. In this context, this work propose a technique to reduce waiting times and optimize quantum computers usage by scheduling circuits from different users into combined circuits that are executed at the same time. To validate this proposal, different widely known quantum algorithms have been selected and executed in combined circuits. The obtained results are then compared with the results of executing the same algorithms in an isolated way. This allowed us to measure the impact of the use of the scheduler. Among the obtained results, it has been possible to verify that the noise suffered by executing a combination of circuits through the proposed scheduler does not critically affect the outcomes.
Progress in the realm of quantum technologies is paving the way for a multitude of potential applications across different sectors. However, the reduced number of available quantum computers, their technical limitations and the high demand for their use are posing some problems for developers and researchers. Mainly, users trying to execute quantum circuits on these devices are usually facing long waiting times in the tasks queues. In this context, this work propose a technique to reduce waiting times and optimize quantum computers usage by scheduling circuits from different users into combined circuits that are executed at the same time. To validate this proposal, different widely known quantum algorithms have been selected and executed in combined circuits. The obtained results are then compared with the results of executing the same algorithms in an isolated way. This allowed us to measure the impact of the use of the scheduler. Among the obtained results, it has been possible to verify that the noise suffered by executing a combination of circuits through the proposed scheduler does not critically affect the outcomes.
Progress in the realm of quantum technologies is paving the way for a multitude of potential applications across different sectors. However, the reduced number of available quantum computers, their technical limitations, and the high demand for their use are posing some problems for developers and researchers. Mainly, users trying to execute quantum circuits on these devices are usually facing long waiting times in the task queues. In this context, this work proposes a Service-Oriented architecture to reduce waiting times and optimize quantum computer usage by scheduling the circuits from different users into combined circuits that are executed at the same time. To validate this proposal, different widely known quantum algorithms have been selected and executed in combined circuits. The obtained results are then compared with the results of executing the same algorithms in an isolated way. This allowed us to measure the impact of the use of the scheduler against quantum noise. Among the obtained results, it has been possible to verify that the noise suffered by executing a combination of circuits through the proposed scheduler does not critically affect the outcomes.
Quantum computing holds significant potential across various fields such as cybersecurity, finance, and health-care, among many others. However, we currently face multiple limitations such as the low availability of computers, the underutilization of available qubits, and the ever-increasing number of users, which results in prolonged waiting times. This, combined with the cost of executions, limits access to quantum computing. To address these challenges, we propose a scheduling process to optimize task execution on quantum computers. The proposed scheduling process unifies multiple circuits to enhance the efficiency of resource utilization in quantum machines. This approach allows for better use of available qubits and reduces the associated execution costs. We validate the proposed method employing various quantum algorithms by systematically examining the scheduling process through a comparative case study between two quantum service providers: IBM Quantum and Amazon Braket. This validation has shown that the scheduling process does not generate a significant impact on the results, ensuring similar results to single circuit executions with a fraction of the cost.
The current execution model of quantum computers, based on serialized task processing, leads to inefficient resource utilization and increased waiting times. This inefficiency persists even as the demand for quantum computing grows. To address this, an automated scheduling approach is proposed through the AutoScheduler library, which replicates quantum circuits to fully occupy the available qubits in a quantum processor. This strategy reduces the number of required shots per execution while optimizing hardware usage. Experimental validation on IBM Quantum and Amazon Braket platforms demonstrates that autoscheduling achieves substantial reductions in execution time and cost, with minimal impact on result fidelity despite inherent quantum noise. These findings suggest that circuit autoscheduling is a viable method for improving the scalability and efficiency of quantum computing in the NISQ era.
Currently, quantum processors offered by quantum service providers are significantly underutilized, resulting in high execution costs and limited scalability. Various approaches have explored parallelization and circuit scheduling techniques to improve resource utilization. While these methods can significantly reduce both cost and execution times, they often have an impact on the results' noise. Addressing this challenge, this emerging study proposes a technique called Quantum Island Mapping, which enables the execution of multiple quantum circuits by separating them into “islands” within the qubit topology of a processor. The goal is to schedule multiple circuits into a single task to reduce execution costs and queuing, while maintaining a controlled separation of qubits between circuits to minimize interferences. To achieve this, separation distance parameters are defined, specifying the minimum number of qubits between different islands. This allows for configurations ranging from zero separation (maximum processor utilization) to maximum separation (single-circuit execution). The technique has been validated through experiments on a real quantum computer using well-known quantum algorithms, achieving optimal results.
Undoubtedly, quantum computing offers valuable acceleration for solving intricate problems. One of the primary hurdles lies in executing large-scale quantum applications on backend machines. Qubit noise, among other factors, dramatically influences the execution process. Implementing effective scheduling techniques for quantum circuits is crucial for practical quantum computing and preventing excessive waiting times. The quantum realm is distinct from classical computing in terms of optimization, performance, utilization, and waiting periods. Consequently, the parameters and components of quantum circuit scheduling diverge from those of classical computing. This paper presents Quantum Noise Mitigation: Introducing the Robust Quantum Circuit Scheduler for Enhanced Fidelity and Throughput, a straightforward yet effective scheduling framework and policy that enhances noise resilience, throughput, and the fidelity of quantum circuits. Drawing inspiration from classical methods, our scheduling approach incorporates additional constraints tailored for quantum logic. The outcome demonstrates a substantial improvement in fidelity and resource management, which is vital for real-world quantum applications.
Quantum computers can solve certain problems faster than classical computers. The number of quantum computers offered via the cloud increases such that a variety is accessible for the public. However, current quantum computers still suffer from a small number of qubits and high error rates. Selecting a quantum computer providing enough qubits and low error rates is tremendously important to receive stable execution results for a given quantum circuit. The execution results are also influenced by the compilation result of the selected quantum compiler for hardware mapping and optimization. For computing time, the access is regulated by vendors of quantum computers resulting in waiting times for the user. Thus, a deep and manifold analysis of quantum computers and compiled circuits of different quantum compilers is required to estimate in advance which compiled circuit will return stable execution results also in consideration of non-functional requirements such as waiting times. To address this, we present a framework that analyzes and prioritizes compiled circuits for different quantum computers using several compilers based on the requirements of the user. We show the practical feasibility of our framework by a prototype and two use cases.