  In the fast-paced field of quantum computing, identifying the architectural
characteristics that will enable quantum processors to achieve high performance
across a diverse range of quantum algorithms continues to pose a significant
challenge. Given the extensive and costly nature of experimentally testing
different designs, this paper introduces the first Design Space Exploration
(DSE) for quantum-dot spin-qubit architectures. Utilizing the upgraded SpinQ
compilation framework, this study explores a substantial design space
comprising 29,312 spin-qubit-based architectures and applies an innovative
optimization tool, ArtA (Artificial Architect), to speed up the design space
traversal. ArtA can leverage 17 optimization configurations, significantly
reducing exploration times by up to 99.1% compared to a traditional brute force
approach while maintaining the same result quality. After a comprehensive
evaluation of best-matching optimization configurations per quantum circuit,
ArtA suggests specific and universal architectural features that provide
optimal performance across the examined circuits. Our work demonstrates that
the synergy between DSE methodologies and optimization algorithms can
effectively be deployed to provide useful suggestions to quantum processor
designers.
