Support trtllm_allreduce_fusion in flashinfer for cuda<12.8 (#9339)

Co-authored-by: Zhang Kaihong <zhangkaihong.zkh@alibaba-inc.com>

python/sglang/srt/layers/communicator.py

@@ -292,7 +292,6 @@ class LayerCommunicator:
             (not self.is_last_layer)
             and (self._context.tp_size > 1)
             and global_server_args_dict.get("enable_flashinfer_allreduce_fusion", False)
-            and _is_sm100_supported
             and _is_flashinfer_available
         )
 

python/sglang/srt/layers/flashinfer_comm_fusion.py

@@ -5,7 +5,11 @@ import torch
 import torch.distributed as dist
 
 from sglang.srt.distributed import get_tensor_model_parallel_world_size
-from sglang.srt.utils import is_flashinfer_available
+from sglang.srt.utils import (
+    direct_register_custom_op,
+    is_flashinfer_available,
+    supports_custom_op,
+)
 
 logger = logging.getLogger(__name__)
 
@@ -196,6 +200,30 @@ def flashinfer_allreduce_residual_rmsnorm(
     return norm_out, residual_out
 
 
+def fake_flashinfer_allreduce_residual_rmsnorm(
+    input_tensor: torch.Tensor,
+    residual: torch.Tensor,
+    weight: torch.Tensor,
+    eps: float = 1e-6,
+    max_token_num: int = 2048,
+    use_oneshot: Optional[bool] = None,
+    trigger_completion_at_end: bool = False,
+    fp32_acc: bool = False,
+) -> Tuple[torch.Tensor, torch.Tensor]:
+    residual_out = torch.empty_like(residual)
+    norm_out = torch.empty_like(input_tensor)
+    return norm_out, residual_out
+
+
+if supports_custom_op():
+    direct_register_custom_op(
+        "flashinfer_allreduce_residual_rmsnorm",
+        flashinfer_allreduce_residual_rmsnorm,
+        mutates_args=["input_tensor", "residual", "weight"],
+        fake_impl=fake_flashinfer_allreduce_residual_rmsnorm,
+    )
+
+
 def cleanup_flashinfer_workspace():
     global _workspace_manager
     if _workspace_manager is not None:

python/sglang/srt/layers/layernorm.py

@@ -27,6 +27,7 @@ from sglang.srt.utils import (
     is_cuda,
     is_hip,
     is_npu,
+    supports_custom_op,
 )
 
 _is_cuda = is_cuda()
@@ -202,8 +203,14 @@ class RMSNorm(CustomOp):
                 flashinfer_allreduce_residual_rmsnorm,
             )
 
+            fused_op = (
+                torch.ops.sglang.flashinfer_allreduce_residual_rmsnorm
+                if supports_custom_op()
+                else flashinfer_allreduce_residual_rmsnorm
+            )
+
             if get_tensor_model_parallel_world_size() > 1:
-                fused_result = flashinfer_allreduce_residual_rmsnorm(
+                fused_result = fused_op(
                     input_tensor=x,
                     residual=residual,
                     weight=self.weight,