Distributed Quantum Computing Resource Allocation and Synchronization
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Solution Overview
Problem
Current quantum computers face challenges in scaling up due to hardware limitations, particularly with qubit count, and there is a need for efficient resource allocation and synchronization in distributed quantum computing systems to enable simultaneous access by multiple users.
Innovation Solution
A system and method for distributed quantum computing that includes a processor and memory configured to receive quantum programs, establish connections with distributed quantum computers, remap and allocate resources, and execute instructions across multiple nodes, optimizing resource utilization and synchronization.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Power
If quantum computers are scaled up by building single systems with more qubits, then computational power increases, but hardware requirements become increasingly challenging to meet
Solution Approach 1:
The patent divides a large-scale quantum computing task into smaller sub-tasks that can be executed on multiple smaller quantum computers. Each quantum computer in the distributed network handles a portion of the overall computation, avoiding the need to build and maintain a single large quantum system with thousands of qubits.
Solution Approach 2:
The patent implements a hierarchical structure where multiple quantum computers are nested within a distributed network framework. The system combines classical control systems with quantum processing units at different levels, creating a nested architecture that leverages both classical and quantum computing capabilities.
2Adaptability or versatility
If distributed quantum computing is implemented, then resource sharing and simultaneous user access improve, but coordination and synchronization complexity increases
Solution Approach 1:
The patent introduces a classical control system as an intermediary that manages coordination between multiple quantum computers. The classical system handles task allocation, timing synchronization, and result aggregation, thereby reducing the direct coordination complexity between quantum processing units.
Solution Approach 2:
The patent implements feedback mechanisms where measurement outputs from quantum computers are collected, processed, and used to adjust subsequent operations. The system continuously monitors quantum state measurements and uses this information to synchronize operations across the distributed network and optimize resource allocation.
3Reliability
If additional operations are injected into algorithm steps for distributed execution, then algorithm equivalence is maintained, but execution time and resource requirements increase
Solution Approach 1:
The patent performs preliminary processing of quantum algorithms to identify and prepare operations that can be executed in parallel across distributed quantum computers. By pre-analyzing the algorithm structure and preparing communication protocols in advance, the system reduces the overhead associated with coordinating distributed execution.
Solution Approach 2:
The patent transforms the execution model from sequential single-system processing to parallel multi-system execution by adding a spatial dimension to the computation. Algorithms are decomposed and distributed across multiple quantum computers, utilizing the spatial arrangement of the network to perform computations simultaneously rather than sequentially.
4Device complexity
If quantum computers operate as individual systems, then system simplicity is maintained, but resource utilization efficiency decreases
Solution Approach 1:
The patent creates a universal quantum computing platform where multiple quantum computers can execute various algorithms and serve multiple users simultaneously. The distributed network provides multi-functional capabilities, allowing the same infrastructure to handle different computational tasks and user requirements, thereby improving resource utilization efficiency.
Data Source
AI summary
A system for distributed quantum computing execution is provided. The system comprises a processor configured to receive at least one user instruction set, process user data to output a flow of quantum programs, determine allocation of available quantum resources need for the flow of quantum programs, remap the flow of programs to the allocation of available quantum resources produce distributed machine level instructions, serialize said distributed machine level instructions, and send the distributed machine level instructions to a distributed quantum computing system. The system further includes a distributed quantum computing system comprising, at least one quantum processing unit configured to receive at least one set of machine level instructions, communicate with a central controller, and send measurement results back to the processor.