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Use device_group for all_gather when disabling overlap scheduling #8001

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Merged
zhyncs merged 1 commit into from
Jul 16, 2025
Merged

Use device_group for all_gather when disabling overlap scheduling #8001

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3 changes: 2 additions & 1 deletion python/sglang/bench_one_batch.py
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Original file line number Diff line number Diff line change
Expand Up @@ -271,12 +271,13 @@ def _maybe_prepare_mlp_sync_batch(batch: ScheduleBatch, model_runner):
batch,
dp_size=model_runner.server_args.dp_size,
attn_tp_size=1,
tp_cpu_group=model_runner.tp_group.cpu_group,
tp_group=model_runner.tp_group,
get_idle_batch=None,
disable_cuda_graph=model_runner.server_args.disable_cuda_graph,
spec_algorithm=SpeculativeAlgorithm.NONE,
speculative_num_draft_tokens=None,
require_mlp_tp_gather=require_mlp_tp_gather(model_runner.server_args),
disable_overlap_schedule=model_runner.server_args.disable_overlap_schedule,
)


Expand Down
16 changes: 13 additions & 3 deletions python/sglang/srt/managers/scheduler.py
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Original file line number Diff line number Diff line change
Expand Up @@ -1826,7 +1826,7 @@ def prepare_mlp_sync_batch(self, local_batch: ScheduleBatch):
local_batch,
dp_size=self.server_args.dp_size,
attn_tp_size=self.attn_tp_size,
tp_cpu_group=self.tp_cpu_group,
tp_group=self.tp_group,
get_idle_batch=self.get_idle_batch,
disable_cuda_graph=self.server_args.disable_cuda_graph,
spec_algorithm=self.spec_algorithm,
Expand All @@ -1835,14 +1835,15 @@ def prepare_mlp_sync_batch(self, local_batch: ScheduleBatch):
enable_deepep_moe=self.server_args.enable_deepep_moe,
deepep_mode=DeepEPMode[self.server_args.deepep_mode],
require_mlp_tp_gather=require_mlp_tp_gather(self.server_args),
disable_overlap_schedule=self.server_args.disable_overlap_schedule,
)

@staticmethod
def prepare_mlp_sync_batch_raw(
local_batch: ScheduleBatch,
dp_size,
attn_tp_size: int,
tp_cpu_group,
tp_group,
get_idle_batch,
disable_cuda_graph: bool,
spec_algorithm,
Expand All @@ -1851,6 +1852,7 @@ def prepare_mlp_sync_batch_raw(
enable_deepep_moe: bool,
deepep_mode: DeepEPMode,
require_mlp_tp_gather: bool,
disable_overlap_schedule: bool,
):
# Check if other DP workers have running batches
if local_batch is None:
Expand Down Expand Up @@ -1881,6 +1883,12 @@ def prepare_mlp_sync_batch_raw(
)

tbo_preparer = TboDPAttentionPreparer()
if disable_overlap_schedule:
group = tp_group.device_group
device = tp_group.device
else:
group = tp_group.cpu_group
device = "cpu"

local_info = torch.tensor(
[
Expand All @@ -1896,15 +1904,17 @@ def prepare_mlp_sync_batch_raw(
),
],
dtype=torch.int64,
device=device,
)
global_info = torch.empty(
(dp_size, attn_tp_size, 6),
dtype=torch.int64,
device=device,
)
torch.distributed.all_gather_into_tensor(
global_info.flatten(),
local_info,
group=tp_cpu_group,
group=group,
)
global_num_tokens = global_info[:, 0, 0].tolist()
can_cuda_graph = min(global_info[:, 0, 1].tolist())
Expand Down
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