[Hardware][Intel GPU] add XPU bf16 support (#12392)

Signed-off-by: Kunshang Ji <kunshang.ji@intel.com>

docs/source/getting_started/installation/gpu/xpu.inc.md

@@ -36,7 +36,7 @@ VLLM_TARGET_DEVICE=xpu python setup.py install
 
 :::{note}
 - FP16 is the default data type in the current XPU backend. The BF16 data
-  type will be supported in the future.
+  type is supported on Intel Data Center GPU, not supported on Intel Arc GPU yet.
 :::
 
 ## Set up using Docker

vllm/platforms/xpu.py

@@ -66,9 +66,14 @@ class XPUPlatform(Platform):
         # check and update model config
         model_config = vllm_config.model_config
         if model_config.dtype == torch.bfloat16:
-            logger.warning(
-                "bfloat16 is not fully supported on XPU, casting to float16.")
-            model_config.dtype = torch.float16
+            bf16_supported = cls.device_support_bf16()
+            if not bf16_supported:
+                logger.warning(
+                    "bfloat16 is only supported on Intel Data Center GPU, "
+                    "Intel Arc GPU is not supported yet. Your device is %s,"
+                    "which is not supported. will fallback to float16",
+                    cls.get_device_name())
+                model_config.dtype = torch.float16
         if not model_config.enforce_eager:
             logger.warning(
                 "CUDA graph is not supported on XPU, fallback to the eager "
@@ -116,3 +121,15 @@ class XPUPlatform(Platform):
                                  ) -> float:
         torch.xpu.reset_peak_memory_stats(device)
         return torch.xpu.max_memory_allocated(device)
+
+    @classmethod
+    def device_support_bf16(cls) -> bool:
+        device_name = cls.get_device_name().lower()
+        if device_name.count("arc") > 0:
+            return False
+        elif device_name.count("data center gpu") > 0:
+            return True
+        else:
+            logger.warning("Unknown device name %s, always use float16",
+                           device_name)
+            return False