[eplb] chunk expert-weight P2P on CUDA to prevent NCCL rebalance hang (#30829)
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@@ -59,8 +59,8 @@ SGLang supports various environment variables that can be used to configure its
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<td style={{padding: "9px 12px", backgroundColor: "rgba(255,255,255,0.02)"}}><code>0</code></td>
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<td style={{padding: "9px 12px", fontWeight: 500, backgroundColor: "rgba(255,255,255,0.02)"}}><code>SGLANG_EPLB_ROCM_P2P_BATCH_CHUNK_SIZE</code></td>
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<td style={{padding: "9px 12px", backgroundColor: "rgba(255,255,255,0.05)"}}>Number of logical expert IDs per batch when submitting P2P ops during EPLB rebalance on ROCm. Smaller values prevent RCCL GPU-side accumulation hangs but increase overhead.</td>
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<td style={{padding: "9px 12px", fontWeight: 500, backgroundColor: "rgba(255,255,255,0.02)"}}><code>SGLANG_EPLB_P2P_BATCH_CHUNK_SIZE</code></td>
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<td style={{padding: "9px 12px", backgroundColor: "rgba(255,255,255,0.05)"}}>Number of expert IDs per batch when submitting P2P ops during EPLB rebalance (CUDA and ROCm). Smaller values prevent NCCL/RCCL GPU-side accumulation hangs but increase overhead; set <code>>= num_physical_experts</code> to submit a single batch. Deprecated alias: <code>SGLANG_EPLB_ROCM_P2P_BATCH_CHUNK_SIZE</code>.</td>
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<td style={{padding: "9px 12px", backgroundColor: "rgba(255,255,255,0.02)"}}><code>32</code></td>
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