Quantum Logic Circuit Decomposition for Heterogeneous Nodes
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Solution Overview
Problem
Current quantum computing systems face challenges in efficiently executing quantum logic circuits due to hardware constraints, such as noisy intermediate-scale quantum (NISQ) technology limitations, which affect hardware compatibility, error rates, and resource utilization, particularly in heterogeneous computing environments.
Innovation Solution
A cost-based circuit decomposition process is employed to break down quantum logic circuits into quantum logic blocks that can be executed concurrently on mixed classical and quantum computing resources, using a 'scatter, gather, update' algorithm, allowing for error recovery and dynamic hardware configuration updates during long-running jobs.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If quantum logic circuits are executed on NISQ hardware, then quantum computational capability is achieved, but hardware compatibility and error rates deteriorate due to hardware constraints
Solution Approach 1:
The quantum logic circuit is decomposed into multiple quantum logic blocks that can be executed independently or concurrently. This segmentation allows the circuit to be adapted to different hardware configurations and reduces the impact of errors in any single block, thereby improving reliability while maintaining hardware compatibility.
Solution Approach 2:
The system dynamically adjusts the execution strategy by selecting between sequential and concurrent execution modes based on hardware availability and error characteristics. This dynamic adaptation allows the system to optimize for reliability when errors are high or for hardware compatibility when resources are constrained.
2Productivity
If quantum logic circuits are decomposed into multiple blocks for concurrent execution, then productivity increases, but device complexity increases due to scheduling and coordination requirements
Solution Approach 1:
The circuit decomposition into quantum logic blocks enables parallel execution on multiple processing nodes, significantly improving productivity. The segmentation is performed in a way that minimizes inter-block dependencies, reducing the scheduling complexity while maintaining the ability to execute blocks concurrently.
Solution Approach 2:
A classical control system acts as an intermediary to manage the decomposition, scheduling, and coordination of quantum logic blocks across multiple processing nodes. This intermediary handles the complexity of concurrent execution, allowing individual blocks to be executed independently while maintaining overall circuit correctness, thus improving productivity without proportionally increasing device complexity.
3Productivity
If execution tasks are dispatched to multiple processing nodes, then hardware utilization increases, but loss of time increases due to coordination and data transfer overhead
Solution Approach 1:
Quantum logic blocks are pre-decomposed and prepared for execution before being dispatched to processing nodes. This preliminary action includes optimizing the decomposition to minimize data transfer requirements and pre-configuring execution tasks, thereby reducing coordination overhead and time loss while maintaining high hardware utilization.
Solution Approach 2:
The system maintains continuous execution by overlapping the preparation of new execution tasks with the execution of current tasks. As quantum logic blocks complete on one processing node, the next blocks are already prepared and ready for immediate dispatch, minimizing idle time and coordination overhead while maximizing hardware utilization across the distributed system.
Data Source
AI summary
In a general aspect, a quantum logic circuit is executed on multiple processing nodes in a computing system that includes quantum computing resources. In some aspects, methods of operating the computing system may include obtaining a computer program that includes a quantum logic circuit. The methods may include obtaining hardware resource metadata specifying properties of processing nodes in the computing system. The processing nodes include at least a subset of the quantum computing resources, and the hardware resource metadata includes error rate information and availability information for the respective processing nodes. The methods may include generating execution tasks configured to execute the quantum logic circuit on the processing nodes based on the hardware resource metadata; dispatching the execution tasks to the processing nodes; receiving output data generated by the processing nodes; and producing an output of the computer program based on the output data.