Frontier: Towards Comprehensive and Accurate LLM Inference Simulation
Modern LLM serving is no longer homogeneous or monolithic. Production systems now combine disaggregated execution, complex parallelism, runtime optimizations, and stateful workloads such as reasoning, agents, and RL rollouts. Simulation is attractive for exploring this growing design space, yet existing simulators lack the architectural completeness and decision-grade fidelity it demands. Their monolithic-replica abstractions are ill-suited to disaggregated serving, while average-case analytical proxies can distort SLA predictions and even reverse optimization conclusions. We present Frontier, a discrete-event simulator for modern LLM inference serving. Frontier features a disaggregated a...
| Authors | Yicheng Feng, Xin Tan, Yangtao Deng et al. |
|---|---|
| Primary category | cs.DC |
| Published | 20 May 2026 |
| Last updated at source | 13 June 2026 |
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