Add Apple silicon GPU(mps) support to ray

python/ray/_private/accelerators/__init__.py

@@ -6,10 +6,12 @@
 from ray._private.accelerators.amd_gpu import AMDGPUAcceleratorManager
 from ray._private.accelerators.tpu import TPUAcceleratorManager
 from ray._private.accelerators.neuron import NeuronAcceleratorManager
+from ray._private.accelerators.apple_gpu import AppleGPUAcceleratorManager
 from ray._private.accelerators.hpu import HPUAcceleratorManager
 from ray._private.accelerators.npu import NPUAcceleratorManager
 
 
+
 def get_all_accelerator_managers() -> Set[AcceleratorManager]:
     """Get all accelerator managers supported by Ray."""
     return {
@@ -18,6 +20,7 @@ def get_all_accelerator_managers() -> Set[AcceleratorManager]:
         AMDGPUAcceleratorManager,
         TPUAcceleratorManager,
         NeuronAcceleratorManager,
+        AppleGPUAcceleratorManager,
         HPUAcceleratorManager,
         NPUAcceleratorManager,
     }
@@ -69,6 +72,7 @@ def get_accelerator_manager_for_resource(
     "AMDGPUAcceleratorManager",
     "TPUAcceleratorManager",
     "NeuronAcceleratorManager",
+    "AppleGPUAcceleratorManager",
     "HPUAcceleratorManager",
     "NPUAcceleratorManager",
     "get_all_accelerator_managers",

python/ray/_private/accelerators/apple_gpu.py

@@ -0,0 +1,51 @@
+import os
+import logging
+from typing import Optional, List, Tuple
+
+from ray._private.accelerators.accelerator import AcceleratorManager
+
+logger = logging.getLogger(__name__)
+
+class AppleGPUAcceleratorManager(AcceleratorManager):
+    """Apple GPU accelerators manager."""
+
+    @staticmethod
+    def get_resource_name() -> str:
+        return "GPU"
+
+    @staticmethod
+    def get_visible_accelerator_ids_env_var() -> str:
+        # There isn't a direct equivalent to CUDA_VISIBLE_DEVICES for Apple Silicon GPUs.
+        # However, the USE_MPS environment variable can be used for enabling MPS support in PyTorch.
+        return "USE_MPS"
+
+    @staticmethod
+    def get_current_node_num_accelerators() -> int:
+        return 1
+
+    @staticmethod
+    def get_current_node_accelerator_type() -> Optional[str]:
+        return "Apple GPU"  # Generic name, as there isn't a specific model like Nvidia's H100
+
+    @staticmethod
+    def validate_resource_request_quantity(quantity: float) -> Tuple[bool, Optional[str]]:
+        if quantity >= 0:
+            return True, None
+        else:
+            return False, "Quantity cannot be negative."
+
+    @staticmethod
+    def get_current_process_visible_accelerator_ids() -> Optional[List[str]]:
+        return None
+
+    @staticmethod
+    def set_current_process_visible_accelerator_ids(ids: List[str]) -> None:
+        pass
+
+    @staticmethod
+    def get_ec2_instance_num_accelerators(instance_type: str, instances: dict) -> Optional[int]:
+        return None
+
+    @staticmethod
+    def get_ec2_instance_accelerator_type(instance_type: str, instances: dict) -> Optional[str]:
+        return None