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

• URL: http://arxiv.org/abs/2504.17886v2
• Date: Mon, 28 Apr 2025 16:45:54 GMT
• Title: TrapSIMD: SIMD-Aware Compiler Optimization for 2D Trapped-Ion Quantum Machines
• Authors: Jixuan Ruan, Hezi Zhang, Xiang Fang, Ang Li, Wesley C. Campbell, Eric Hudson, David Hayes, Hartmut Haeffner, Travis Humble, Jens Palsberg, Yufei Ding,
• Abstract summary: We present FluxTrap, a SIMD-aware compiler framework that establishes a hardware-software co-design interface for TI systems.<n>F FluxTrap reduces execution time by up to $3.82 times$ and improves fidelity by several orders of magnitude.
• Score: 14.239863509836864
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• 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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