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arXiv · 2504.17886

TrapSIMD: SIMD-Aware Compiler Optimization for 2D Trapped-Ion Quantum Machines

Jixuan Ruan·Hezi Zhang·Xiang Fang·Ang Li·Wesley C. Campbell·Eric Hudson·David Hayes·Hartmut Haeffner·Travis Humble·Jens Palsberg·Yufei Ding
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Abstract

Modular trapped-ion (TI) architectures offer a scalable quantum computing (QC) platform, with native transport behaviors that closely resemble the Single Instruction Multiple Data (SIMD) paradigm. We present FluxTrap, a SIMD-aware compiler framework that establishes a hardware-software co-design interface for TI systems. FluxTrap introduces a novel abstraction that unifies SIMD-style instructions -- including segmented intra-trap shift SIMD (S3) and global junction transfer SIMD (JT-SIMD) operations -- with a SIMD-enriched architectural graph, capturing key features such as transport synchronization, gate-zone locality, and topological constraints. It applies two passes -- SIMD aggregation and scheduling -- to coordinate grouped ion transport and gate execution within architectural constraints. On NISQ benchmarks, FluxTrap reduces execution time by up to $3.82 \times$ and improves fidelity by several orders of magnitude. It also scales to fault-tolerant workloads under diverse hardware configurations, providing feedback for future TI hardware design.

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Jixuan Ruan, Hezi Zhang, Xiang Fang, Ang Li, Wesley C. Campbell, Eric Hudson, David Hayes, Hartmut Haeffner, Travis Humble, Jens Palsberg, Yufei Ding. 2025-04-24. TrapSIMD: SIMD-Aware Compiler Optimization for 2D Trapped-Ion Quantum Machines. https://arxiv.org/abs/2504.17886

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