Quantum Resource Parceling With Auction-Based Qubit Scheduling
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Solution Overview
Problem
Existing technologies face challenges in efficiently partitioning and virtualizing monolithic quantum-classical hybrid computing resources into multiple saleable parcels, particularly in managing qubits and qubit-qubit links for multi-tenancy and demand-based workload processing.
Innovation Solution
A method for dynamically partitioning and virtualizing quantum-classical hybrid computing resources into parcels, including qubits and qubit-qubit links, with a system for order matching, auctioning, and scheduling to allocate resources based on user demands, using a CPU scheduler for thread-level control and synchronization, and a user interface for resource selection and monitoring.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If monolithic quantum-classical hybrid computing resources are partitioned and virtualized into multiple parcels, then resource utilization efficiency and multi-tenancy support are improved, but system complexity and difficulty of managing qubit allocation increase
Solution Approach 1:
The patent divides monolithic quantum-classical hybrid computing resources into multiple independently saleable parcels, where each parcel contains specific qubits and qubit-qubit links. This segmentation allows different users to rent different parcels for different computational tasks, thereby improving resource utilization efficiency while managing system complexity through structured partitioning.
Solution Approach 2:
The patent introduces a resource manager as an intermediary component that handles order matching, auctioning, and scheduling of quantum resources. This mediator coordinates between multiple users and the quantum computing system, managing the complexity of qubit allocation and parcel distribution while enabling efficient resource utilization through automated decision-making.
2Adaptability or versatility
If quantum resources are dynamically allocated based on user demand through auctioning and scheduling, then adaptability to different workloads is improved, but resource allocation time and scheduling overhead increase
Solution Approach 1:
The patent implements preliminary action by pre-defining quantum resource parcels with specific configurations of qubits and links before user requests arrive. The system prepares multiple parcel options in advance that can be quickly matched to user demands, reducing allocation time while maintaining adaptability to different workload requirements through pre-configured parcel varieties.
Solution Approach 2:
The patent applies dynamics by implementing a flexible auctioning and scheduling mechanism that can adapt parcel allocation in real-time based on user demands and system state. The resource manager dynamically adjusts which parcels are allocated to which users, allowing the system to be versatile across different workloads while managing allocation time through efficient dynamic decision-making processes.
Data Source
AI summary
In a general aspect, methods and systems are described for dynamically partitioning and virtualizing a monolithic quantum-classical hybrid computing resource into multiple different and independently-saleable, as a resource to a user, parcels. These parcels may comprise configurations of qubits and qubit-qubit links on one or more quantum processor units for use by users for running computer programs.