Asynchronous Quantum Program Execution for Low-Dead-Time QPUs
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Solution Overview
Problem
Existing quantum information processing methods suffer from significant dead time and inefficiencies due to serial execution of parameter sets, leading to underutilization of quantum processing units (QPUs) and prolonged convergence times.
Innovation Solution
An asynchronous method is implemented where multiple parameter sets are determined and executed concurrently on QPUs, allowing immediate updates based on real-time results, reducing dead time and enabling continuous operation of QPUs.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If serial execution of parameter sets is used, then the quantum processing unit can be controlled in a simple manner, but significant dead time occurs and the QPU is underutilized
Solution Approach 1:
The system pre-calculates multiple parameter sets (e.g., 3-5 parameter sets) before QPU execution and stores them in a queue. This preliminary preparation eliminates the need for real-time parameter calculation during QPU operation, thereby removing dead time and ensuring continuous QPU operation while maintaining simple control architecture.
Solution Approach 2:
By maintaining a queue of pre-calculated parameter sets, the QPU can execute quantum programs continuously without idle periods. The controller loads the next parameter set from the queue immediately after the current one completes, ensuring the QPU operates at full capacity throughout the optimization process.
2Ease of operation
If serial execution of parameter sets is used, then the control process is straightforward, but convergence time is prolonged
Solution Approach 1:
Multiple parameter sets are pre-calculated and stored in a queue before QPU execution begins. This eliminates waiting time during the optimization process, as the controller can immediately load the next parameter set from the pre-prepared queue, significantly reducing total convergence time while keeping the control process simple.
Solution Approach 2:
The system dynamically adjusts the parameter queue based on QPU performance and convergence criteria. As the optimization progresses, the controller can modify the queue contents or size based on real-time feedback, enabling adaptive acceleration of the convergence process without complicating the overall control architecture.
3Productivity
If multiple parameter sets are executed concurrently, then QPU utilization increases, but system complexity increases
Solution Approach 1:
Multiple parameter sets are pre-calculated and stored in a simple queue structure before execution. This approach enables concurrent execution of multiple parameter sets without requiring complex real-time coordination, as the queue provides a straightforward mechanism for managing multiple executions while maintaining simple controller logic.
4Reliability
If more samples are processed, then solution confidence increases, but processing time increases in serial execution
Solution Approach 1:
The QPU operates continuously without idle periods by executing quantum programs for multiple parameter sets back-to-back from a pre-loaded queue. This continuous operation increases the total number of samples processed within the same time frame, thereby improving solution confidence without extending processing time.
Solution Approach 2:
The system dynamically determines when to execute additional parameter sets based on convergence criteria and solution confidence requirements. The controller can adjust the number of parameter sets in the queue and the execution schedule in real-time, enabling flexible optimization of both processing speed and solution reliability based on problem requirements.
Data Source
AI summary
An asynchronous approach to implementing a quantum algorithm can reduce dead time of a quantum information processing unit (QIPU). Multiple parameter sets are determined for a quantum program by a controller and the QIPU is instructed to execute the quantum program for the parameter sets. Results from each program execution are returned to the controller. After one or more results are received, the controller determines an updated parameter set while the QIPU continues executing the quantum program for the remaining parameter sets. The QIPU is instructed to execute the quantum program for the updated parameter set (e.g., immediately, after a current program execution, or after the remaining parameter sets are processed). This asynchronous approach can result in the QIPU having little or no dead time, and thus can make more efficient use of the QIPU.