Cross-Backend QIEO: Universal Runtime Portability across OpenMP5, CUDA, HIP, and Multi-Language Interfaces

arXiv:2609.30914 · cs.DC, cs.CL, math.OC · Submitted 2026-09-25 · Read on arXiv

cs.DC, cs.CL, math.OC

Submitted: 2026-09-25

Updated: 2026-09-25

Code: https://github.com/pybind/pybind11

Terminology

• Accuracy — 17× in this paper · explained in 1 episode
• Core — 15× in this paper · explained in 2 episodes
• Benchmark — 11× in this paper · explained in 2 episodes
• Calibration — 8× in this paper · explained in 7 episodes
• Abstraction — 7× in this paper · explained in 1 episode
• BQP — 7× in this paper · explained in 2 episodes
• Hardware Abstraction Layer — 4× in this paper
• Actor — 3× in this paper · explained in 3 episodes
• Classical Information Processing — 2× in this paper
• Consistency — 2× in this paper · explained in 3 episodes
• Objective Function — 2× in this paper · explained in 2 episodes
• Abundance — 1× in this paper · explained in 1 episode
• Adaptation — 1× in this paper · explained in 1 episode
• Alignment — 1× in this paper · explained in 1 episode
• Bayesian Optimization — 1× in this paper · explained in 3 episodes
• Benchmarking — 1× in this paper · explained in 3 episodes
• Clustering — 1× in this paper · explained in 2 episodes
• Combinatorial Optimization — 1× in this paper · explained in 2 episodes
• Decoupling — 1× in this paper · explained in 2 episodes
• Domain Adaptation — 1× in this paper · explained in 5 episodes
• Fidelity — 1× in this paper · explained in 2 episodes
• Hybrid System — 1× in this paper · explained in 2 episodes
• Pruning — 1× in this paper · explained in 4 episodes
• Quantum Information Processing — 1× in this paper
• Scaffolding — 1× in this paper · explained in 3 episodes
• Trace — 1× in this paper · explained in 2 episodes

Sources

• Benchmarking of GPU-optimized Quantum-Inspired Evolutionary Optimization Algorithm using Functional Analysis

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