Hybrid Quantum-Classical Block Staging for Time Reduction
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Solution Overview
Problem
Current quantum computing systems face challenges in efficiently staging quantum computations, leading to increased total computation time.
Innovation Solution
A hybrid computing system comprising a classical computing system and a quantum computing system maps computational problems into quantum and classical blocks, allowing for their execution and reordering to reduce total computation time.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of time
If quantum computations are executed sequentially without blocking, then computation completeness is ensured, but total computation time increases
Solution Approach 1:
The patent divides the quantum computation into discrete quantum blocks and classical blocks that can be independently executed and reused. This segmentation allows the computation to be staged efficiently across quantum and classical processors, reducing total execution time while managing complexity through modular organization.
Solution Approach 2:
The patent implements a blocking mechanism where quantum operations are blocked until their results are needed by subsequent classical blocks. This preliminary blocking allows the system to execute classical computations in parallel while waiting for quantum results, thereby reducing overall computation time without requiring complex coordination.
2Reliability
If quantum blocks are executed immediately without blocking, then execution speed is improved, but computation accuracy and dependency tracking deteriorate
Solution Approach 1:
The patent employs a feedback mechanism where the completion status of quantum blocks is fed back to the execution engine. This allows the system to track which quantum blocks have completed and which are still running, enabling accurate dependency management and ensuring that classical blocks wait for required quantum results while maintaining execution speed through parallel processing.
Solution Approach 2:
The system performs preliminary blocking of quantum operations until their results are available, ensuring computational accuracy. This preliminary action allows the execution engine to maintain accurate tracking of computation dependencies while still enabling efficient parallel execution of independent classical blocks.
3Productivity
If computational problems are mapped to quantum blocks without historical modeling, then mapping simplicity is maintained, but block selection optimality deteriorates
Solution Approach 1:
The patent implements historical modeling that records the performance and characteristics of quantum and classical blocks from previous executions. This preliminary action allows the execution engine to make optimal block selection decisions based on historical data, improving productivity while keeping the mapping process simple through automated learning rather than complex manual configuration.
Solution Approach 2:
The system performs self-service by automatically learning from historical execution data and using this information to optimize future block mappings. This self-service mechanism improves block selection optimality without requiring complex external configuration, as the system adapts to workload patterns autonomously.
Data Source
AI summary
According to an embodiment of the present invention, a method, system, and computer program product are described. An embodiment may receive, by a hybrid computing system comprising a classical computing system and a quantum computing system, a computational problem. The embodiment may map, by the classical system, a portion of the computational problem to quantum blocks and a portion of the computation problem to classical blocks. The embodiment may execute the quantum blocks and classical blocks.