[EPLB] Offline eplb support#26176
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Signed-off-by: Patryk Saffer <patryk.saffer99@gmail.com>
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Signed-off-by: PatrykSaffer <patryk.saffer@mistral.ai>
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Signed-off-by: PatrykSaffer <patryk.saffer@mistral.ai>
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This pull request has been automatically marked as stale because it has not had any activity within 90 days. It will be automatically closed if no further activity occurs within 30 days. Leave a comment if you feel this pull request should remain open. Thank you! |
# Conflicts: # vllm/config/parallel.py # vllm/distributed/eplb/eplb_state.py # vllm/model_executor/layers/fused_moe/fused_moe.py # vllm/model_executor/layers/fused_moe/fused_moe_method_base.py # vllm/model_executor/layers/fused_moe/fused_moe_modular_method.py # vllm/model_executor/layers/fused_moe/layer.py # vllm/model_executor/layers/fused_moe/unquantized_fused_moe_method.py # vllm/model_executor/layers/quantization/awq_marlin.py # vllm/model_executor/layers/quantization/bitsandbytes.py # vllm/model_executor/layers/quantization/compressed_tensors/compressed_tensors_moe.py # vllm/model_executor/layers/quantization/experts_int8.py # vllm/model_executor/layers/quantization/fp8.py # vllm/model_executor/layers/quantization/gguf.py # vllm/model_executor/layers/quantization/gptq_marlin.py # vllm/model_executor/layers/quantization/ipex_quant.py # vllm/model_executor/layers/quantization/modelopt.py # vllm/model_executor/layers/quantization/moe_wna16.py # vllm/model_executor/layers/quantization/mxfp4.py # vllm/model_executor/layers/quantization/quark/quark_moe.py # vllm/model_executor/layers/quantization/rtn.py # vllm/model_executor/models/qwen3_moe.py # vllm/v1/worker/gpu_model_runner.py
Signed-off-by: Patryk Saffer <patryk.saffer99@gmail.com>
Signed-off-by: Patryk Saffer <patryk.saffer99@gmail.com>
Signed-off-by: Patryk Saffer <patryk.saffer99@gmail.com>
Signed-off-by: Patryk Saffer <patryk.saffer99@gmail.com>
Signed-off-by: Patryk Saffer <patryk.saffer99@gmail.com>
Signed-off-by: Patryk Saffer <patryk.saffer99@gmail.com>
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Hello @abmfy could you please review? |
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Purpose
Offline eplb- make it possible to rearrange experts once at the start time.
This allows rebalancing experts when engine starts. With
staticexperts are rebalanced only once when engine starts,this allows better experts balancedness without metrics tracking/rearrangement overhead.
EPLB has more options now:
load_initial_load_windowandload_path:Whether to use initial load window and corresponding path.
save_load_windowandload_path:Whether to save load window and corresponding path.
static:Whether to actively rebalance experts during runtime.
Test Plan
Integration test test_eplb_offline.py added.
Test Result
Tests pass