Hybrid Quantum Workload Orchestration for Low-Latency Cloud Execution
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing hybrid quantum/classical computing systems face challenges in efficiently managing and executing workloads due to high network latency and resource allocation inefficiencies, particularly in cloud-based environments where user devices are remotely located from quantum computing resources.
Innovation Solution
A hybrid quantum/classical computing system architecture that includes low-latency communication pathways and dynamic resource allocation, utilizing virtualized environments such as containers and quantum processing units (QPUs) to optimize workload orchestration and execution, especially in cloud-based settings.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If cloud-based quantum computing resources are used, then accessibility and scalability are improved, but network latency and execution time increase
Solution Approach 1:
The patent introduces a quantum cloud gateway as an intermediary component that sits between user devices and quantum computing resources. This gateway manages connections, handles authentication, and optimizes data transmission, thereby reducing network latency while maintaining cloud-based accessibility. The gateway acts as a local proxy that can cache frequently accessed quantum resources and pre-process requests.
Solution Approach 2:
The system performs preliminary actions by pre-loading quantum computing environments and resources before they are actually needed. Virtual quantum machines are instantiated and prepared in advance, and quantum algorithms are compiled and optimized beforehand. This reduces the time required when users actually access these resources, mitigating network latency effects.
2Productivity
If virtualized quantum computing environments are used, then resource utilization and scalability are improved, but system complexity increases
Solution Approach 1:
The patent implements a universal quantum virtual machine architecture that can run multiple quantum workloads simultaneously on shared hardware resources. This virtualization layer provides multi-functionality by allowing different quantum algorithms, different quantum hardware backends, and different user applications to share the same physical quantum computing resources efficiently, thereby improving resource utilization without proportionally increasing system complexity.
Solution Approach 2:
The quantum virtual machine includes self-service capabilities for automatic resource allocation, load balancing, and error handling. The system automatically manages the complexity of resource provisioning and configuration, reducing the burden on users and operators while maintaining high resource utilization. The virtualization manager handles resource orchestration autonomously.
3Productivity
If dynamic resource allocation is implemented, then execution efficiency is improved, but control complexity increases
Solution Approach 1:
The patent implements feedback mechanisms where the quantum computing system continuously monitors resource usage, queue lengths, and execution performance. Based on this feedback, the resource allocator dynamically adjusts resource distribution, prioritizes tasks, and makes real-time scheduling decisions. This feedback loop enables efficient execution by adapting to actual system conditions rather than relying on static allocation rules.
Solution Approach 2:
The system employs dynamic resource allocation where computing resources are not statically assigned but are instead flexibly reallocated based on current workload demands. Quantum processors, memory, and I/O resources are dynamically provisioned to matching tasks in real-time. This dynamic approach improves execution efficiency by ensuring resources are available when needed without requiring over-provisioning for peak loads.
Data Source
AI summary
In some aspects, a cloud-based computer system includes: a quantum computing system comprising a quantum processing unit; a container management and execution system configured to receive a container and execute a program within the container; and a communication channel between the container management and execution system and the quantum computing system for providing program instructions to the quantum computing system. The container management and execution system and the quantum computer system may be co-located in a data center or located in different data centers. The latency of the communication channel may be selected to optimize cost for a required computer performance.