enable prefix cache with dp (#10459)

python/sglang/srt/model_executor/model_runner.py

@@ -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.")
 

python/sglang/srt/models/deepseek_v2.py

@@ -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