[bugfix] remove the EP buffer allocation introduced by fused-op dispatch_ffn_c… (#5284)
### What this PR does / why we need it?
- This PR removes the Expert Parallel (EP) HCCL buffer allocation that
was previously introduced by the fused-op `dispatch_ffn_combine` (#3532
), since the fused-op has switch to MC2 HCCL buffer (#5156 ).
### Does this PR introduce _any_ user-facing change?
### How was this patch tested?
- vLLM version: release/v0.13.0
- vLLM main:
ad32e3e19c
Signed-off-by: Chen Chen <0109chenchen@gmail.com>
This commit is contained in:
@@ -941,9 +941,6 @@ def get_hccl_config_for_pg_options(group_name: str) -> Optional[dict]:
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"dp": {
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"hccl_buffer_size": calculate_dp_buffer_size()
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},
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"ep": {
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"hccl_buffer_size": calculate_ep_buffer_size()
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},
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}
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return hccl_config_map.get(group_name, get_default_buffer_config())
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@@ -965,31 +962,6 @@ def calculate_dp_buffer_size() -> int:
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return max(dp_buffer_size, _MIN_DP_BUFFER_SIZE)
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def calculate_ep_buffer_size() -> int:
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"""
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formula of ep buffer size:
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batch_size * hidden_size * topk * 4
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"""
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ep_buffer_size = _DEFAULT_BUFFER_SIZE
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try:
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from vllm.config import get_current_vllm_config
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vllm_config = get_current_vllm_config()
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tp_size = vllm_config.parallel_config.tensor_parallel_size
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hf_config = vllm_config.model_config.hf_config
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hidden_size = hf_config.hidden_size
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topk = getattr(hf_config, "num_experts_per_tok", 1)
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batch_size = vllm_config.scheduler_config.max_num_batched_tokens // tp_size
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int8_size = torch.iinfo(torch.int8).bits // 8
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bf16_size = torch.finfo(torch.bfloat16).bits // 8
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ep_buffer_size = math.ceil(
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(batch_size * hidden_size * topk *
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(int8_size + bf16_size) * 3) / (1024 * 1024))
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except Exception:
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pass
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return max(ep_buffer_size, _DEFAULT_BUFFER_SIZE)
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# Currently, when in A2, setting the environment variables HCCL_INTRA_PCIE_ENABLE=1
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# and HCCL_INTRA_ROCE_ENABLE=0 can reduce cross-machine communication traffic and
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# significantly improve communication performance of MC2 ops dispatch/combine.
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