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[PP] Fix dynamic chunking strategy for PP #15372

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Merged
ShangmingCai merged 1 commit into from
Dec 18, 2025
Merged

[PP] Fix dynamic chunking strategy for PP #15372

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23 changes: 13 additions & 10 deletions python/sglang/srt/managers/scheduler_pp_mixin.py
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Original file line number Diff line number Diff line change
Expand Up @@ -10,6 +10,7 @@
import numpy as np
import torch
import torch.distributed
from tqdm import tqdm

from sglang.srt.disaggregation.base.conn import KVPoll
from sglang.srt.disaggregation.utils import DisaggregationMode, poll_and_all_reduce
Expand Down Expand Up @@ -532,13 +533,11 @@ def profile_and_init_predictor(self: Scheduler):
latencies: List[float] = []

if self.pp_group.is_first_rank:
logger.info("Profiling prefill latency for dynamic chunk sizing...")

# Create requests with different lengths: base_chunk_size // (2**i) for i in range(10)
input_ids_list = []
for i in range(32):
chunk_size = self.chunked_prefill_size - i * (
self.chunked_prefill_size // 32
for i in range(128):
chunk_size = int(
self.chunked_prefill_size * 1.25
- i * (self.chunked_prefill_size * 1.25 // 128)
)
if chunk_size <= 0:
break
Expand All @@ -551,9 +550,13 @@ def profile_and_init_predictor(self: Scheduler):
temperature=0,
max_new_tokens=1,
)

# Create and profile requests
for i, input_ids in enumerate(input_ids_list):
for i, input_ids in enumerate(
tqdm(
input_ids_list,
desc="Profiling prefill latency for dynamic chunking",
)
):
req = Req(
rid=str(i),
origin_input_text="",
Expand Down Expand Up @@ -1338,8 +1341,8 @@ def predict_next_chunk_size(
)
calculated_chunk_size = int(smoothed_chunk_size)

# Align to page_size (round down to nearest multiple)
alignment_size = max(page_size, 1)
# Align to page_size (minimum alignment size is 64)
alignment_size = max(page_size, 64)
dynamic_chunk_size = (calculated_chunk_size // alignment_size) * alignment_size

# Ensure aligned size is at least alignment_size
Expand Down
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