Revati: Transparent GPU-Free Time-Warp Emulation for LLM Serving

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Authors: Amey Agrawal, Yadav, Mayank, Sukrit Kumar, Anirudha Agrawal, Garv Ghai, Souradeep Bera, Pinto, Elton, Sirish Gambhira, Mohammad Adain, Kasra Sohrab, Chus Antonanzas, Alexey Tumanov
Cited by: 0

Abstract

Deploying LLMs efficiently requires testing hundreds of serving configurations, but evaluating each one on a GPU cluster takes hours and costs thousands of dollars. Discrete-event simulators are faster and cheaper, but they require re-implementing the serving system's control logic -- a burden that compounds as frameworks evolve. We present Revati, a time-warp emulator that enables performance modeling by directly executing real serving system code at simulation-like speed. The system intercepts CUDA API calls to virtualize device management, allowing serving frameworks to run without physical GPUs. Instead of executing GPU kernels, it performs time jumps -- fast-forwarding virtual time by predicted kernel durations. We propose a coordination protocol that synchronizes these jumps across distributed processes while preserving causality. On vLLM and SGLang, Revati achieves less than 5% prediction error across multiple models and parallelism configurations, while running 5-17x faster than real GPU execution.

Fields of Study & Subjects

Parallel Computing and Optimization Techniques Advanced Data Storage Technologies Software System Performance and Reliability

Publication details

Journal / source
arXiv (Cornell University)
Publication date
1 January 2026
Document type
Preprint