UNIFERENCE: A Discrete Event Simulation Framework for Developing Distributed AI Models
Developing and evaluating distributed inference algorithms remains difficult due to the lack of standardized tools for modeling heterogeneous devices and networks. Existing studies often rely on ad-hoc testbeds or proprietary infrastructure, making results hard to reproduce and limiting exploration of hypothetical hardware or network configurations. We present UNIFERENCE, a discrete-event simulation (DES) framework designed for developing, benchmarking, and deploying distributed AI models within a unified environment. UNIFERENCE models device and network behavior through lightweight logical processes that synchronize only on communication primitives, eliminating rollbacks while preserving...
| Authors | Doğaç Eldenk, Stephen Xia |
|---|---|
| Primary category | cs.DC |
| Published | 27 March 2026 |
| Last updated at source | 27 March 2026 |
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