refactor: abstract deepgemm support into platform (#37519)

Co-authored-by: sherryC41 <sherry.c.c41@gmail.com>

vllm/platforms/cuda.py

@@ -511,6 +511,11 @@ class CudaPlatformBase(Platform):
     def support_static_graph_mode(cls) -> bool:
         return True
 
+    @classmethod
+    def support_deep_gemm(cls) -> bool:
+        """Currently, only Hopper and Blackwell GPUs are supported."""
+        return cls.is_device_capability(90) or cls.is_device_capability_family(100)
+
     @classmethod
     def num_compute_units(cls, device_id: int = 0) -> int:
         return torch.cuda.get_device_properties(device_id).multi_processor_count

vllm/platforms/interface.py

@@ -712,6 +712,13 @@ class Platform:
         """
         return False
 
+    @classmethod
+    def support_deep_gemm(cls) -> bool:
+        """
+        Returns if DeepGEMM is supported by the current platform.
+        """
+        return False
+
     @classmethod
     def use_custom_op_collectives(cls) -> bool:
         """

vllm/utils/deep_gemm.py

@@ -70,10 +70,7 @@ def is_deep_gemm_supported() -> bool:
     """Return `True` if DeepGEMM is supported on the current platform.
     Currently, only Hopper and Blackwell GPUs are supported.
     """
-    is_supported_arch = current_platform.is_cuda() and (
-        current_platform.is_device_capability(90)
-        or current_platform.is_device_capability_family(100)
-    )
+    is_supported_arch = current_platform.support_deep_gemm()
     return envs.VLLM_USE_DEEP_GEMM and has_deep_gemm() and is_supported_arch