QBAIX: A Hybrid Deterministic Architecture for High-Performance Compute Systems Abstract : High Performance Computing (HPC) systems today are primarily built using multi-node CPU and GPU clusters. While these systems deliver high computational throughput, they require significant infrastructure, including complex networking fabrics, high power consumption, and specialized operational management. At the same time, quantum computing research promises transformative performance but remains largely experimental and commercially inaccessible. This paper introduces QBAIX, a hybrid classical high-performance compute architecture designed to optimize execution efficiency within a single integrated node. QBAIX combines multi-socket CPU density, high-memory GPU acceleration, structure-aware workload routing through M-OS, and embedded execution governance through UNI-OS. Instead of increasing raw hardware scale through cluster expansion, QBAIX improves compute efficiency by intelligent workload classification and intra-node task routing. The architecture emphasizes reduced fabric dependency, improved GPU utilization, lower synchronization overhead, and integrated execution isolation. QBAIX does not introduce a new quantum processor, nor does it claim quantum equivalence. Rather, it proposes a deployable classical architecture that narrows the practical performance-efficiency gap between conventional HPC clusters and future quantum research platforms. The paper presents the architectural model, execution framework, workload routing methodology, benchmark positioning, and deployment strategy of QBAIX as a hybrid classical compute system optimized for the AI-driven era.
Mandale Raaj (Sun,) studied this question.