Enabling AI Network Cross-Layer Design and Operations with Arcadia...
summary
Arcadia is a calibrated, multi‑fidelity discrete‑event simulator that replays production traces to answer counterfactuals about schedulers, transports, hardware, and operations. It supports packet/flow/packing models, runs a 4,000‑host, eight‑H100‑per‑host evaluation, and reports about 5% error (packing) and ~58.8x speedup vs. AstraSim. It fast‑forwards stable iterations, lets teams plug in custom modules, models PFC/ECN/queues for buffer and QP experiments, and has guided 50+ production decisions over three years.
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chapters (14)
- 0:00Arcadia AI network simulator
- 1:01AI infrastructure reasoning
- 3:46AI cluster design challenges
- 5:32Production testing limits
- 6:55Simulator requirements
- 8:39Arcadia meets requirements
- 10:03Design principles
- 11:49Multi-fidelity modeling
- 13:15Continuous calibration
- 14:20Accuracy and performance
- 15:25Hardware what-if analysis
- 16:32QP scaling evaluation
- 17:39Future directions
- 18:20Key takeaways
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