Quantum compilation is a multi-pass process that translates a high-level circuit into an equivalent one executable on quantum hardware. A critical stage in this process is mapping, where additional gates are inserted to satisfy hardware constraints. Current mapping techniques often suffer from significant performance degradation—in terms of added gate count, increased circuit depth, and longer compilation times that scale with circuit size. In this work, we propose a novel methodology that enhances quantum compilation by leveraging concepts from Electronic Design Automation. Our approach partitions a quantum circuit into sub-circuits that can be compiled independently, and reformulates the mapping problem as a temporal floorplanning instance—a well-established technique in classical circuit design. We validate our method on widely used quantum circuit benchmark suites, achieving an average depth reduction of 22.05 % compared to traditional monolithic compilation chains using IBM Qiskit. Moreover, our approach reduces overall compilation time to that required for compiling the largest partition, while our partitioning-floorplanning algorithm runs, on average, two orders of magnitude faster than compiling the full circuit.
Improving Quantum Compilation via Circuit Partitioning and Floorplanning
Lancellotti, Giacomo;Agosta, Giovanni;Barenghi, Alessandro;Pelosi, Gerardo
2025-01-01
Abstract
Quantum compilation is a multi-pass process that translates a high-level circuit into an equivalent one executable on quantum hardware. A critical stage in this process is mapping, where additional gates are inserted to satisfy hardware constraints. Current mapping techniques often suffer from significant performance degradation—in terms of added gate count, increased circuit depth, and longer compilation times that scale with circuit size. In this work, we propose a novel methodology that enhances quantum compilation by leveraging concepts from Electronic Design Automation. Our approach partitions a quantum circuit into sub-circuits that can be compiled independently, and reformulates the mapping problem as a temporal floorplanning instance—a well-established technique in classical circuit design. We validate our method on widely used quantum circuit benchmark suites, achieving an average depth reduction of 22.05 % compared to traditional monolithic compilation chains using IBM Qiskit. Moreover, our approach reduces overall compilation time to that required for compiling the largest partition, while our partitioning-floorplanning algorithm runs, on average, two orders of magnitude faster than compiling the full circuit.| File | Dimensione | Formato | |
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