Distributed Quantum Computing Resource Scheduling
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Solution Overview
Problem
Existing distributed quantum computing systems face challenges in efficiently managing user requests for accessing quantum computing resources, particularly in optimizing resource allocation and ensuring seamless execution of quantum jobs.
Innovation Solution
A computer-implemented method and system where a server manages user requests by selecting appropriate quantum processing units (QPUs) or quantum virtual machines (QVMs) based on availability, user preferences, and performance metrics, and schedules computing jobs to optimize resource utilization.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If distributed quantum computing resources are allocated to multiple users simultaneously, then resource utilization and productivity improve, but managing user requests and ensuring seamless execution becomes more complex
Solution Approach 1:
A server acts as an intermediary between users and quantum processing units/QVMs. The server receives user requests, selects appropriate quantum resources based on availability and performance metrics, and manages job scheduling. This intermediary layer simplifies request management while enabling efficient multi-user resource utilization.
2Adaptability or versatility
If quantum processing units and virtual machines are dynamically selected based on availability and performance, then system adaptability and productivity improve, but the complexity of resource selection and scheduling increases
Solution Approach 1:
The system uses performance metrics and availability status as feedback to dynamically select quantum resources. The server monitors the state of QPUs and QVMs, and this feedback information guides the selection process to optimize resource allocation based on current system conditions and user preferences.
Solution Approach 2:
The resource selection and scheduling system is dynamic rather than static. The server can adaptively choose between different QPUs and QVMs based on real-time availability and performance metrics, allowing the system to respond to changing conditions and optimize resource utilization dynamically.
3Adaptability or versatility
If quantum jobs are executed on remote quantum computing resources, then access versatility improves, but ensuring reliable and seamless execution becomes more difficult
Solution Approach 1:
The server serves as a reliable intermediary that manages the complexity of remote quantum job execution. It handles user authentication, selects appropriate quantum resources, submits jobs to the quantum computing backend, and retrieves results. This intermediary layer shields users from the complexity of remote execution while ensuring reliable job completion.
Data Source
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AI summary
In a general aspect, user requests for access distributed quantum computing resources in a distributed quantum computing system are managed. In a general aspect, a job request for accessing a quantum computing resource is received. The job request includes a user id and a program. On authentication of a user associated with the job request, a job identifier is assigned to the job request, and a particular quantum computing resource is selected for the job request. The job request is individualized based on user permissions and pushed onto a queue to be processed for execution by the quantum computing resource.