[Perf] refactor attention backend for perf boost

vllm/config/scheduler.py

@@ -159,6 +159,10 @@
     structured outputs, speculative decoding, and pipeline parallelism.
     """
 
+    split_prefill_from_chunk: bool = False
+    """Whether to split the prefill request into pure prefill and chunked prefill in a single
+    batch."""
+
     def compute_hash(self) -> str:
         """
         WARNING: Whenever a new field is added to this config,

vllm/platforms/rocm.py

@@ -340,6 +340,10 @@
                 else:
                     parallel_config.worker_cls = "vllm.worker.worker.Worker"
 
+        if envs.VLLM_ROCM_USE_AITER and envs.VLLM_ROCM_USE_AITER_MHA:
+            # enable the request reorder if we are using AITER MHA for calculation
+            vllm_config.scheduler_config.split_prefill_from_chunk = True
+
     @classmethod
     def verify_model_arch(cls, model_arch: str) -> None:
         if model_arch in _ROCM_UNSUPPORTED_MODELS: