Quantum Instruction Scheduling With Pulse-Level Latency Reduction
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Solution Overview
Problem
Existing quantum computing systems face significant challenges in reducing computation latency due to inefficiencies in classical compilation techniques, which lead to mismatches between logical gates and physical hardware capabilities, especially for large numbers of qubits.
Innovation Solution
A quantum compilation engine that optimizes quantum programs by segmenting scheduling operations into smaller problems, performing logical blocking, and strategically grouping instructions to foster parallelism and align with physical hardware constraints, ultimately generating optimized control pulses for execution on a quantum processor.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If quantum programs are compiled into quantum assembly instructions using conventional gate-based approaches, then a universal set of operations is achieved, but computation latency increases significantly
Solution Approach 1:
The patent segments the compilation process into multiple stages: logical assembly generation, physical mapping, and pulse optimization. This segmentation allows each stage to be optimized independently, reducing overall latency while maintaining universality through the logical assembly intermediate representation.
Solution Approach 2:
The patent introduces logical assembly instructions as an intermediary between high-level quantum programs and physical hardware operations. This intermediary layer enables optimization of the compilation process by providing a standardized intermediate representation that can be efficiently translated to various physical implementations.
2Ease of manufacture
If logical assembly instructions are directly translated to control pulses, then implementation simplicity is maintained, but hardware efficiency is reduced due to mismatch between logical gates and physical operations
Solution Approach 1:
The patent uses logical assembly instructions as an intermediary that bridges the gap between universal logical gates and hardware-specific physical operations. This intermediary enables efficient translation to hardware-native operations while maintaining the simplicity of a standardized logical interface.
Solution Approach 2:
The patent changes the parameters of instruction representation by introducing logical assembly with specific structural properties (blocks, commutativity relationships) that enable more efficient hardware mapping and pulse generation, improving hardware efficiency without complicating the implementation.
3Loss of time
If aggregation of logical assembly instructions is performed, then parallelism is fostered and latency is reduced, but the complexity of scheduling increases
Solution Approach 1:
The patent segments instructions into logical blocks with identified commutativity relationships, enabling systematic aggregation of compatible instructions. This segmentation approach manages scheduling complexity by providing a structured method for identifying parallelizable operations.
Solution Approach 2:
The patent changes the scheduling approach by incorporating commutativity analysis as a key parameter. Instructions are aggregated based on their commutativity properties, which provides a clear criterion for parallel execution and reduces scheduling complexity while maximizing parallelism.
Data Source
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AI summary
A quantum computing system includes a quantum processor having a plurality of qubits, a classical memory, and a classical processor. The classical processor is configured to compile a quantum program into logical assembly instructions in an intermediate language, aggregate the logical assembly instructions together into a plurality of logical blocks of instructions, generate a logical schedule for the quantum program based on commutativity between the plurality of logical blocks, generate a tentative physical schedule based on the logical schedule, the tentative physical schedule includes a mapping of the logical assembly instructions in the logical schedule onto the plurality of qubits of the quantum processor, aggregate instructions together within the tentative physical schedule that do not reduce parallelism, thereby generating an updated physical schedule; generate optimized control pulses for the aggregated instructions, and execute the quantum program on the quantum processor with the optimized control pulses and the updated physical schedule.