[Intel GPU] Add XPU Platform support (#31949)

Signed-off-by: P V R K Jyothendra Varma <polisetty.v.r.k.jyothendra.varma@intel.com>
Co-authored-by: Ma Mingfei <mingfei.ma@intel.com>

python/sglang/srt/platforms/__init__.py

@@ -22,6 +22,7 @@ from sglang.srt.platforms.cpu import CpuSRTPlatform
 from sglang.srt.platforms.cuda import CudaSRTPlatform
 from sglang.srt.platforms.interface import SRTPlatform
 from sglang.srt.platforms.rocm import RocmSRTPlatform
+from sglang.srt.platforms.xpu import XpuSRTPlatform
 from sglang.srt.plugins import PLATFORM_PLUGINS_GROUP, load_plugins_by_group
 
 logger = logging.getLogger(__name__)
@@ -41,6 +42,10 @@ def _is_cpu_available() -> bool:
     return os.getenv("SGLANG_USE_CPU_ENGINE", "0") == "1"
 
 
+def _is_xpu_available() -> bool:
+    return torch.xpu.is_available()
+
+
 def _resolve_platform() -> SRTPlatform:
     """
     Discover and instantiate the active platform.
@@ -62,6 +67,7 @@ def _resolve_platform() -> SRTPlatform:
            so developers on GPU hosts can intentionally exercise the CPU path)
          - 0 activated + CUDA available → fallback CudaSRTPlatform
          - 0 activated + ROCm available → fallback RocmSRTPlatform
+         - 0 activated + XPU available  → fallback XpuSRTPlatform
          - 0 activated + none of the above → fallback base SRTPlatform
          - 1 activated → use it
          - N activated → RuntimeError (must set SGLANG_PLATFORM)
@@ -126,6 +132,9 @@ def _resolve_platform() -> SRTPlatform:
                 "No platform plugin detected. Using ROCm SRTPlatform defaults."
             )
             return RocmSRTPlatform()
+        if _is_xpu_available():
+            logger.debug("No platform plugin detected. Using XPU SRTPlatform defaults.")
+            return XpuSRTPlatform()
         logger.debug("No platform detected. Using base SRTPlatform.")
         return SRTPlatform()
 

python/sglang/srt/platforms/xpu.py

@@ -0,0 +1,104 @@
+"""XPU device operations for the SRT platform layer."""
+
+import logging
+from typing import Optional
+
+import torch
+
+from sglang.srt.platforms.device_mixin import (
+    DeviceCapability,
+    DeviceMixin,
+    PlatformEnum,
+)
+from sglang.srt.platforms.interface import SRTPlatform
+
+logger = logging.getLogger(__name__)
+
+
+class XpuDeviceMixin(DeviceMixin):
+    """XPU implementation of the shared device operations."""
+
+    _enum: PlatformEnum = PlatformEnum.XPU
+    device_name: str = "xpu"
+    device_type: str = "xpu"
+
+    def get_device_total_memory(self, device_id: int = 0) -> int:
+        return int(torch.xpu.get_device_properties(device_id).total_memory)
+
+    def get_current_memory_usage(
+        self, device: Optional["torch.device"] = None
+    ) -> float:
+        return float(torch.xpu.max_memory_allocated(device))
+
+    def get_device(self, local_rank: int) -> "torch.device":
+        return torch.device("xpu", local_rank)
+
+    def set_device(self, device: "torch.device") -> None:
+        torch.xpu.set_device(device)
+
+    def get_device_name(self, device_id: int = 0) -> str:
+        return str(torch.xpu.get_device_name(device_id))
+
+    def get_device_uuid(self, device_id: int = 0) -> str:
+        return str(torch.xpu.get_device_properties(device_id).uuid)
+
+    def get_device_capability(self, device_id: int = 0) -> DeviceCapability:
+        # TODO: torch.xpu.get_device_capability
+        device = torch.xpu.current_device()
+        major, minor = torch.ops.sgl_kernel.query_device.default(device)
+        return DeviceCapability(major, minor)
+
+    def empty_cache(self) -> None:
+        torch.xpu.empty_cache()
+
+    def synchronize(self) -> None:
+        torch.xpu.synchronize()
+
+    def get_available_memory(self, device_id: int = 0) -> tuple[int, int]:
+        # TODO: simple return of torch.xpu.mem_get_info
+        """Return the available and total device memory in Bytes."""
+
+        if not (hasattr(torch, "xpu") and torch.xpu.is_available()):
+            return 0, 0
+
+        num_gpus = torch.xpu.device_count()
+        if device_id < 0 or device_id >= num_gpus:
+            raise ValueError(f"Invalid XPU device_id={device_id}. num_gpus={num_gpus}")
+
+        current = torch.xpu.current_device()
+        if current != device_id:
+            logger.warning(
+                "current device is not %s, but %s; this may cause useless memory allocation for torch XPU context.",
+                device_id,
+                current,
+            )
+
+        used_memory = torch.xpu.memory_allocated(device_id)
+        total_gpu_memory = torch.xpu.get_device_properties(device_id).total_memory
+        free_gpu_memory = total_gpu_memory - used_memory
+
+        return free_gpu_memory, total_gpu_memory
+
+    def is_pin_memory_available(self, device=None) -> bool:
+        if device is not None and str(device) == "cpu":
+            return False
+        return True
+
+    @classmethod
+    def seed_everything(cls, seed: int | None = None) -> None:
+        if seed is not None:
+            super().seed_everything(seed)
+            torch.xpu.manual_seed_all(seed)
+
+
+class XpuSRTPlatform(XpuDeviceMixin, SRTPlatform):
+    """Default in-tree XPU SRT platform."""
+
+    def supports_fp8(self) -> bool:
+        return False
+
+    def support_cuda_graph(self) -> bool:
+        return True
+
+    def support_piecewise_cuda_graph(self) -> bool:
+        return True