Three Phases of Expert Routing: How Load Balance Evolves During Mixture-of-Experts Training

1. 1Identify the surge phase where the router learns to balance load
2. 2Analyze the transition phase where the router adapts to changing congestion
3. 3Optimize the convergence phase for stable and efficient expert routing

AI engineers and researchers working on Mixture-of-Experts models can benefit from understanding these phases to improve model performance and efficiency

💡 The congestion coefficient gamma_eff is a key parameter in understanding the balance-quality tradeoff in MoE token routing

🚀 3 phases of MoE expert routing: surge, transition, & convergence! 🤖