Full-Stack, Real-System Quantum Computer Studies: Architectural Comparisons and Design Insights

Abstract: In recent years, Quantum Computing (QC) has progressed to the point where small working prototypes are available for use. Termed Noisy Intermediate-Scale Quantum (NISQ) computers, these prototypes are too small for large benchmarks or even for Quantum Error Correction, but they do have sufficient resources to run small benchmarks, particularly if compiled with optimizations to make use of scarce qubits and limited operation counts and coherence times. QC has not yet, however, settled on a particular preferred device implementation technology, and indeed different NISQ prototypes implement qubits with very different physical approaches and therefore widely-varying device and machine characteristics. Our work performs a full-stack, benchmark-driven hardware-software analysis of QC systems. We evaluate QC architectural possibilities, software-visible gates, and software optimizations to tackle fundamental design questions about gate set choices, communication topology, the factors affecting benchmark performance and compiler optimizations. In order to answer key cross-technology and cross-platform design questions, our work has built the first top-to-bottom toolflow to target different qubit device technologies, including superconducting and trapped ion qubits which are the current QC front-runners. We use our toolflow, TriQ, to conduct {\em real-system} measurements on 7 running QC prototypes from 3 different groups, IBM, Rigetti, and University of Maryland. From these real-system experiences at QC's hardware-software interface, we make observations about native and software-visible gates for different QC technologies, communication topologies, and the value of noise-aware compilation even on lower-noise platforms. This is the largest cross-platform real-system QC study performed thus far; its results have the potential to inform both QC device and compiler design going forward.

Full-Stack, Real-System Quantum Computer Studies: Insights into Quantum Architecture and Compilation

The paper "Full-Stack, Real-System Quantum Computer Studies: Architectural Comparisons and Design Insights" presents an empirical study of quantum computing (QC) systems through a comprehensive full-stack approach, analyzing both hardware and software layers. The study meticulously evaluates Noisy Intermediate-Scale Quantum (NISQ) computers which represent emerging small-scale quantum systems with intrinsic noise limitations. The authors perform a benchmark-driven analysis across different quantum architectures, emphasizing the critical interplay between device characteristics, gate choices, communication topology, and noise adaptivity through a cross-platform tool named \compilername.

Key Contributions and Findings

1. Cross-Technology Benchmarking: The paper represents the first extensive cross-platform benchmarking of operational QC prototypes from leading entities including IBM, Rigetti, and the University of Maryland. The evaluations are conducted on systems employing superconducting and trapped ion qubit technologies, which are the forerunners in the field. By leveraging real-system runs, the study highlights the strengths and limitations of different quantum device implementations.
2. Gate and Communication Optimization: The authors demonstrate that optimizing quantum programs to better align with the native gate sets of the underlying hardware can significantly improve computational success rates. Notably, software-visible operations that closely reflect hardware-native gates permit substantial compile-time optimizations. For example, the study reported up to a 28-fold increase in program success rates on IBM's device when using noise-aware compilation strategies.
3. Noise and Error Adaptivity: The research introduces noise-aware compilation, which leverages real-time calibration data to inform quantum circuit mapping decisions. This adaptivity is essential for mitigating the impact of temporal and spatial error variability inherent in current NISQ devices. Noise-aware mappings resulted in up to 1.47x improvement in success rate on systems like UMD's ion trap when compared to noise-agnostic approaches.
4. Toolflow Scalability and Generalization: \compilername, developed for this study, presents a generalized and scalable compilation framework capable of adapting to the diverse architectural peculiarities of quantum devices. The toolflow effectively supports multi-platform optimizations, proving scalable up to the largest publicly announced NISQ configurations, such as Google's proposed 72-qubit system.
5. Implications for Quantum Architecture and Design: Through systematic evaluations, the paper provides insights that could guide future QC technology developments. A primary recommendation is for QC systems to expose their native gate operations more transparently to compilers, allowing for enriched optimization opportunities. Additionally, architectural design must consider qubit communication topologies, as they significantly impact program success—particularly in devices with limited connectivity.

Implications and Future Directions

This research has profound implications for both practical and theoretical quantum computing. Practically, it provides tangible evidence of how compiler optimizations tailored to hardware characteristics can dramatically enhance NISQ system performance, a critical consideration as quantum computers transition from experimental to practical applications. Theoretically, it opens further inquiries into how future advancements in quantum error correction and scalable architectures might further benefit from such a consolidated hardware-software interface approach.

Future developments in AI and quantum computing could build on these explorations, fostering advancements in fields requiring vast computational power, such as drug discovery, cryptography, and complex systems simulation. By highlighting the nuanced tradeoffs between different qubit technologies and architectural strategies, this study gives a quintessential roadmap for navigating the intricate landscape of quantum technology evolution.

Overall, this paper underscores the necessity for a holistic approach in quantum computer design, where the synthesis of hardware capabilities and software strategies is pivotal for harnessing the full potential of quantum processors.