EngineX-Hygon/sglang
5
0
Fork 0
Code Issues Pull Requests Actions 7 Projects Releases Wiki Activity

enable prefix cache with dp (#10459)

Browse Source
This commit is contained in:
Shu Wang
2025-09-16 20:26:58 -05:00
committed by GitHub
parent e1d45bc280
commit 124097fc5b
2 changed files with 0 additions and 30 deletions
Download Patch File Download Diff File Expand all files Collapse all files

12
python/sglang/srt/model_executor/model_runner.py
View File

@@ -564,18 +564,6 @@ class ModelRunner:
if not self.use_mla_backend:
server_args.disable_chunked_prefix_cache = True
# TODO(kaixih@nvidia): remove this once we have a better solution for DP attention.
# For more details, see: https://github.com/sgl-project/sglang/issues/8616
elif (
self.dp_size > 1
and is_sm100_supported()
and server_args.attention_backend != "triton"
and server_args.attention_backend == "trtllm_mla"
):
logger.info(
"Disable chunked prefix cache when dp size > 1 and attention backend is not triton."
)
server_args.disable_chunked_prefix_cache = True
if not server_args.disable_chunked_prefix_cache:
logger.info("Chunked prefix cache is turned on.")

18
python/sglang/srt/models/deepseek_v2.py
View File

@@ -1098,7 +1098,6 @@ class DeepseekV2AttentionMLA(nn.Module):
attention_backend == "flashinfer" or attention_backend == "flashmla"
) and self.flashinfer_mla_disable_ragged
original_mode = getattr(forward_batch, "_original_forward_mode", None)
if (
not disable_ragged
and forward_batch.forward_mode.is_extend()
@@ -1111,15 +1110,6 @@ class DeepseekV2AttentionMLA(nn.Module):
)
or sum_extend_prefix_lens == 0
)
# TODO(shuw@nvidia.com) Flashinfer cutlass and trtllm_mla backend have accuracy issue on blackwell for
# dp case. Redirect to mla kernel as a workaround.
# Tracked by https://github.com/sgl-project/sglang/issues/9806.
and not (
original_mode is not None
and original_mode.is_decode()
and is_sm100_supported()
and self.current_attention_backend in ("cutlass_mla", "flashinfer")
)
):
return AttnForwardMethod.MHA_CHUNKED_KV
else:
@@ -1128,14 +1118,6 @@ class DeepseekV2AttentionMLA(nn.Module):
# TODO(cicirori): use FA4 MHA for DeepSeekV3 for now
return AttnForwardMethod.MHA_CHUNKED_KV
elif attention_backend == "trtllm_mla":
original_mode = getattr(forward_batch, "_original_forward_mode", None)
if (
original_mode is not None
and original_mode.is_decode()
and is_sm100_supported()
):
return _dispatch_mla_subtype()
sum_extend_prefix_lens = (
sum(forward_batch.extend_prefix_lens_cpu)
if forward_batch.extend_prefix_lens_cpu is not None