Fault-tolerant quantum computing (FTQC) is emerging as the architectural regime in which practical large-scale quantum workloads will execute. In this setting, however, multiprogramming is no longer a matter of partitioning a flat pool of qubits. Quantum error correction exposes a structured floorplan of data tiles, ancilla tiles, and magic-state service resources, so concurrent execution must account for compact placement, connectivity, routing headroom, and shared support infrastructure. This makes FTQC multiprogramming fundamentally harder than its NISQ counterpart: admission decisions can fragment the remaining floorplan, conservative reservations can waste ancilla, and dynamic contention across data, ancilla, and magic-state resources can degrade both throughput and quality of service. In this work, we develop a formal framework for FTQC multiprogramming that captures these structural constraints and their runtime implications. We formulate the baseline static allocation problem, extend it to limited-resource and online settings through hierarchy-aware scheduling policies, and further generalize it to cultivation-enabled architectures with dynamic magic-state generation. Through simulation on synthetic Clifford+T workloads, the proposed scheduler achieves a normalized system speedup of 3.1x, improving over prior FTQC multiprogramming baselines by ~29% while maintaining low mean slowdown.

翻译：容错量子计算（FTQC）正成为实际大规模量子工作负载运行的架构范式。然而在此设定下，多道程序技术不再仅仅是划分平坦量子比特池的问题。量子纠错暴露了由数据块、辅助块和魔法态服务资源组成的结构化布局，因此并发执行必须考虑紧凑放置、连接性、路由裕度以及共享支撑基础设施。这使得FTQC多道程序技术从根本上比NISQ对应技术更困难：准入决策可能碎片化剩余布局，保守预留可能浪费辅助空间，而数据、辅助和魔法态资源间的动态争用会降低吞吐量和服务质量。本文为FTQC多道程序技术开发了一个形式化框架，捕捉了这些结构约束及其运行时影响。我们形式化了基线静态分配问题，通过层次感知调度策略将其扩展到资源受限和在线设置，并进一步推广到具有动态魔法态生成能力的 cultivation 使能架构。通过对合成 Clifford+T 工作负载的仿真，所提出的调度器实现了3.1倍的归一化系统加速比，相较现有FTQC多道程序基线提升约29%，同时保持了较低的平均减速比。