[core] Add tags parameter to wake_up() (#15500)

Signed-off-by: Eric <erictang000@gmail.com>

tests/basic_correctness/test_cumem.py

@@ -155,6 +155,24 @@ def test_end_to_end(monkeypatch: pytest.MonkeyPatch, model: str, use_v1: bool):
 
         llm.wake_up()
         output2 = llm.generate(prompt, sampling_params)
-
         # cmp output
         assert output[0].outputs[0].text == output2[0].outputs[0].text
+
+        llm.sleep(level=1)
+        llm.wake_up(tags=["weights"])
+
+        free_gpu_bytes_wake_up_w, total = torch.cuda.mem_get_info()
+        used_bytes = total - free_gpu_bytes_wake_up_w - used_bytes_baseline
+
+        # should just reallocate memory for weights (1B model, ~2GiB weights)
+        if use_v1:
+            assert used_bytes < 10 * GiB_bytes
+        else:
+            assert used_bytes < 6 * GiB_bytes
+
+        # now allocate kv cache memory
+        llm.wake_up(tags=["kv_cache"])
+        output3 = llm.generate(prompt, sampling_params)
+
+        # cmp output
+        assert output[0].outputs[0].text == output3[0].outputs[0].text

tests/entrypoints/openai/test_sleep.py

@@ -25,16 +25,37 @@ def test_sleep_mode():
                                 "VLLM_SERVER_DEV_MODE": "1",
                                 "CUDA_VISIBLE_DEVICES": "0"
                             }) as remote_server:
-
-        response = requests.post(remote_server.url_for("/sleep"),
+        response = requests.post(remote_server.url_for("sleep"),
                                  params={"level": "1"})
         assert response.status_code == 200
-        response = requests.get(remote_server.url_for("/is_sleeping"))
+        response = requests.get(remote_server.url_for("is_sleeping"))
         assert response.status_code == 200
         assert response.json().get("is_sleeping") is True
 
-        response = requests.post(remote_server.url_for("/wake_up"))
+        response = requests.post(remote_server.url_for("wake_up"))
         assert response.status_code == 200
-        response = requests.get(remote_server.url_for("/is_sleeping"))
+        response = requests.get(remote_server.url_for("is_sleeping"))
+        assert response.status_code == 200
+        assert response.json().get("is_sleeping") is False
+
+        # test wake up with tags
+        response = requests.post(remote_server.url_for("sleep"),
+                                 params={"level": "1"})
+        assert response.status_code == 200
+
+        response = requests.post(remote_server.url_for("wake_up"),
+                                 params={"tags": ["weights"]})
+        assert response.status_code == 200
+
+        # is sleeping should be false after waking up any part of the engine
+        response = requests.get(remote_server.url_for("is_sleeping"))
+        assert response.status_code == 200
+        assert response.json().get("is_sleeping") is True
+
+        response = requests.post(remote_server.url_for("wake_up"),
+                                 params={"tags": ["kv_cache"]})
+        assert response.status_code == 200
+
+        response = requests.get(remote_server.url_for("is_sleeping"))
         assert response.status_code == 200
         assert response.json().get("is_sleeping") is False

vllm/device_allocator/cumem.py

@@ -208,22 +208,28 @@ class CuMemAllocator:
         gc.collect()
         torch.cuda.empty_cache()
 
-    def wake_up(self):
+    def wake_up(self, tags: Optional[list[str]] = None) -> None:
         """
         Wake up the allocator from sleep mode.
         All data that is previously offloaded will be loaded back to GPU 
-        memory, and the rest of the data will have empty memory."""
+        memory, and the rest of the data will have empty memory.
+        
+        :param tags: The tags of the memory allocation that will be loaded
+            back to GPU memory. If None, all memory allocation will be loaded
+            back to GPU memory.
+        """
         for ptr, data in self.pointer_to_data.items():
-            handle = data.handle
-            create_and_map(handle)
-            if data.cpu_backup_tensor is not None:
-                cpu_backup_tensor = data.cpu_backup_tensor
-                if cpu_backup_tensor is not None:
-                    size_in_bytes = cpu_backup_tensor.numel(
-                    ) * cpu_backup_tensor.element_size()
-                    cpu_ptr = cpu_backup_tensor.data_ptr()
-                    libcudart.cudaMemcpy(ptr, cpu_ptr, size_in_bytes)
-                    data.cpu_backup_tensor = None
+            if tags is None or data.tag in tags:
+                handle = data.handle
+                create_and_map(handle)
+                if data.cpu_backup_tensor is not None:
+                    cpu_backup_tensor = data.cpu_backup_tensor
+                    if cpu_backup_tensor is not None:
+                        size_in_bytes = cpu_backup_tensor.numel(
+                        ) * cpu_backup_tensor.element_size()
+                        cpu_ptr = cpu_backup_tensor.data_ptr()
+                        libcudart.cudaMemcpy(ptr, cpu_ptr, size_in_bytes)
+                        data.cpu_backup_tensor = None
 
     @contextmanager
     def use_memory_pool(self, tag: Optional[str] = None):

vllm/engine/async_llm_engine.py

@@ -1225,8 +1225,8 @@ class AsyncLLMEngine(EngineClient):
     async def sleep(self, level: int = 1) -> None:
         self.engine.sleep(level)
 
-    async def wake_up(self) -> None:
-        self.engine.wake_up()
+    async def wake_up(self, tags: Optional[list[str]] = None) -> None:
+        self.engine.wake_up(tags)
 
     async def is_sleeping(self) -> bool:
         return self.engine.is_sleeping()

vllm/engine/llm_engine.py

@@ -1938,10 +1938,10 @@ class LLMEngine:
             "Sleep mode is not enabled in the model config")
         self.model_executor.sleep(level=level)
 
-    def wake_up(self) -> None:
+    def wake_up(self, tags: Optional[list[str]] = None) -> None:
         assert self.vllm_config.model_config.enable_sleep_mode, (
             "Sleep mode is not enabled in the model config")
-        self.model_executor.wake_up()
+        self.model_executor.wake_up(tags)
 
     def is_sleeping(self) -> bool:
         return self.model_executor.is_sleeping

vllm/engine/multiprocessing/__init__.py

@@ -133,8 +133,9 @@ class RPCSleepRequest(Enum):
     SLEEP_LEVEL_2 = 2
 
 
-class RPCWakeUpRequest(Enum):
-    WAKE_UP = 1
+@dataclass
+class RPCWakeUpRequest:
+    tags: Optional[list[str]] = None
 
 
 @dataclass

vllm/engine/multiprocessing/client.py

@@ -697,10 +697,10 @@ class MQLLMEngineClient(EngineClient):
         return await self._send_one_way_rpc_request(
             request=RPCSleepRequest(level), socket=self.input_socket)
 
-    async def wake_up(self) -> None:
+    async def wake_up(self, tags: Optional[list[str]] = None) -> None:
         """Wake up the engine"""
         return await self._send_one_way_rpc_request(
-            request=RPCWakeUpRequest.WAKE_UP, socket=self.input_socket)
+            request=RPCWakeUpRequest(tags), socket=self.input_socket)
 
     async def is_sleeping(self) -> bool:
         """Check whether the engine is sleeping"""

vllm/engine/multiprocessing/engine.py

@@ -274,7 +274,7 @@ class MQLLMEngine:
                 elif isinstance(request, RPCSleepRequest):
                     self.sleep(request.value)
                 elif isinstance(request, RPCWakeUpRequest):
-                    self.wake_up()
+                    self.wake_up(request.tags)
                 elif isinstance(request, RPCIsSleepingRequest):
                     self._handle_is_sleeping_request(request)
                 else:
@@ -415,8 +415,8 @@ class MQLLMEngine:
     def sleep(self, level: int = 1) -> None:
         self.engine.sleep(level)
 
-    def wake_up(self) -> None:
-        self.engine.wake_up()
+    def wake_up(self, tags: Optional[list[str]] = None) -> None:
+        self.engine.wake_up(tags)
 
     def is_sleeping(self) -> bool:
         return self.engine.is_sleeping()

vllm/engine/protocol.py

@@ -282,7 +282,7 @@ class EngineClient(ABC):
         ...
 
     @abstractmethod
-    async def wake_up(self) -> None:
+    async def wake_up(self, tags: Optional[list[str]] = None) -> None:
         """Wake up the engine"""
         ...
 

vllm/entrypoints/llm.py

@@ -1200,26 +1200,35 @@ class LLM:
         The caller should guarantee that no requests are being processed
         during the sleep period, before `wake_up` is called.
 
-        :param level: The sleep level. Level 1 sleep will offload the model 
-            weights and discard the kv cache. The content of kv cache is 
-            forgotten. Level 1 sleep is good for sleeping and waking up the 
-            engine to run the same model again. The model weights are backed 
-            up in CPU memory. Please make sure there's enough CPU memory to 
-            store the model weights. Level 2 sleep will discard both the model 
-            weights and the kv cache. The content of both the model weights 
-            and kv cache is forgotten. Level 2 sleep is good for sleeping and 
-            waking up the engine to run a different model or update the model, 
-            where previous model weights are not needed. It reduces CPU memory 
-            pressure.
+        Args:
+            level: The sleep level. Level 1 sleep will offload the model 
+                weights and discard the kv cache. The content of kv cache 
+                is forgotten. Level 1 sleep is good for sleeping and waking
+                up the engine to run the same model again. The model weights 
+                are backed up in CPU memory. Please make sure there's enough 
+                CPU memory to store the model weights. Level 2 sleep will 
+                discard both the model weights and the kv cache. The content 
+                of both the model weights and kv cache is forgotten. Level 2 
+                sleep is good for sleeping and waking up the engine to run a
+                different model or update the model, where previous model 
+                weights are not needed. It reduces CPU memory pressure.
         """
         self.reset_prefix_cache()
         self.llm_engine.sleep(level=level)
 
-    def wake_up(self):
+    def wake_up(self, tags: Optional[list[str]] = None):
         """
         Wake up the engine from sleep mode. See the :meth:`sleep` method
-        for more details."""
-        self.llm_engine.wake_up()
+        for more details.
+        
+        Args:
+            tags: An optional list of tags to reallocate the engine memory 
+                for specific memory allocations. Values must be in 
+                ("weights", "kv_cache",). If None, all memory is reallocated.
+                wake_up should be called with all tags (or None) before the 
+                engine is used again.
+        """
+        self.llm_engine.wake_up(tags)
 
     # LEGACY
     def _convert_v1_inputs(

vllm/entrypoints/openai/api_server.py

@@ -705,7 +705,6 @@ if envs.VLLM_SERVER_DEV_MODE:
     async def sleep(raw_request: Request):
         # get POST params
         level = raw_request.query_params.get("level", "1")
-        logger.info("sleep the engine with level %s", level)
         await engine_client(raw_request).sleep(int(level))
         # FIXME: in v0 with frontend multiprocessing, the sleep command
         # is sent but does not finish yet when we return a response.
@@ -713,8 +712,12 @@ if envs.VLLM_SERVER_DEV_MODE:
 
     @router.post("/wake_up")
     async def wake_up(raw_request: Request):
-        logger.info("wake up the engine")
-        await engine_client(raw_request).wake_up()
+        tags = raw_request.query_params.getlist("tags")
+        if tags == []:
+            # set to None to wake up all tags if no tags are provided
+            tags = None
+        logger.info("wake up the engine with tags: %s", tags)
+        await engine_client(raw_request).wake_up(tags)
         # FIXME: in v0 with frontend multiprocessing, the wake-up command
         # is sent but does not finish yet when we return a response.
         return Response(status_code=200)

vllm/executor/executor_base.py

@@ -51,6 +51,7 @@ class ExecutorBase(ABC):
         self.observability_config = vllm_config.observability_config
         self._init_executor()
         self.is_sleeping = False
+        self.sleeping_tags: set[str] = set()
 
     @abstractmethod
     def _init_executor(self) -> None:
@@ -204,20 +205,34 @@ class ExecutorBase(ABC):
         time_before_sleep = time.perf_counter()
         self.collective_rpc("sleep", kwargs=dict(level=level))
         time_after_sleep = time.perf_counter()
+        self.sleeping_tags = {"weights", "kv_cache"}
         self.is_sleeping = True
         logger.info("It took %.6f seconds to fall asleep.",
                     time_after_sleep - time_before_sleep)
 
-    def wake_up(self):
+    def wake_up(self, tags: Optional[list[str]] = None):
         if not self.is_sleeping:
             logger.warning("Executor is not sleeping.")
             return
+        if tags:
+            for tag in tags:
+                if tag not in self.sleeping_tags:
+                    logger.warning("Tag %s is not in sleeping tags %s", tag,
+                                   self.sleeping_tags)
+                    return
         time_before_wakeup = time.perf_counter()
-        self.collective_rpc("wake_up")
+        self.collective_rpc("wake_up", kwargs=dict(tags=tags))
         time_after_wakeup = time.perf_counter()
-        self.is_sleeping = False
-        logger.info("It took %.6f seconds to wake up.",
-                    time_after_wakeup - time_before_wakeup)
+        logger.info("It took %.6f seconds to wake up tags %s.",
+                    time_after_wakeup - time_before_wakeup,
+                    tags if tags is not None else self.sleeping_tags)
+        if tags:
+            for tag in tags:
+                self.sleeping_tags.remove(tag)
+        else:
+            self.sleeping_tags.clear()
+        if not self.sleeping_tags:
+            self.is_sleeping = False
 
     def save_sharded_state(
         self,

vllm/v1/engine/async_llm.py

@@ -424,8 +424,8 @@ class AsyncLLM(EngineClient):
     async def sleep(self, level: int = 1) -> None:
         await self.engine_core.sleep_async(level)
 
-    async def wake_up(self) -> None:
-        await self.engine_core.wake_up_async()
+    async def wake_up(self, tags: Optional[list[str]] = None) -> None:
+        await self.engine_core.wake_up_async(tags)
 
     async def is_sleeping(self) -> bool:
         return await self.engine_core.is_sleeping_async()

vllm/v1/engine/core.py

@@ -264,8 +264,8 @@ class EngineCore:
     def sleep(self, level: int = 1):
         self.model_executor.sleep(level)
 
-    def wake_up(self):
-        self.model_executor.wake_up()
+    def wake_up(self, tags: Optional[list[str]] = None):
+        self.model_executor.wake_up(tags)
 
     def is_sleeping(self) -> bool:
         return self.model_executor.is_sleeping

vllm/v1/engine/core_client.py

@@ -92,7 +92,7 @@ class EngineCoreClient(ABC):
     def sleep(self, level: int = 1) -> None:
         raise NotImplementedError
 
-    def wake_up(self) -> None:
+    def wake_up(self, tags: Optional[list[str]] = None) -> None:
         raise NotImplementedError
 
     def is_sleeping(self) -> bool:
@@ -141,7 +141,7 @@ class EngineCoreClient(ABC):
     async def sleep_async(self, level: int = 1) -> None:
         raise NotImplementedError
 
-    async def wake_up_async(self) -> None:
+    async def wake_up_async(self, tags: Optional[list[str]] = None) -> None:
         raise NotImplementedError
 
     async def is_sleeping_async(self) -> bool:
@@ -206,8 +206,8 @@ class InprocClient(EngineCoreClient):
     def sleep(self, level: int = 1) -> None:
         self.engine_core.sleep(level)
 
-    def wake_up(self) -> None:
-        self.engine_core.wake_up()
+    def wake_up(self, tags: Optional[list[str]] = None) -> None:
+        self.engine_core.wake_up(tags)
 
     def is_sleeping(self) -> bool:
         return self.engine_core.is_sleeping()
@@ -520,8 +520,8 @@ class SyncMPClient(MPClient):
     def sleep(self, level: int = 1) -> None:
         self.call_utility("sleep", level)
 
-    def wake_up(self) -> None:
-        self.call_utility("wake_up")
+    def wake_up(self, tags: Optional[list[str]] = None) -> None:
+        self.call_utility("wake_up", tags)
 
     def is_sleeping(self) -> bool:
         return self.call_utility("is_sleeping")
@@ -647,8 +647,8 @@ class AsyncMPClient(MPClient):
     async def sleep_async(self, level: int = 1) -> None:
         await self.call_utility_async("sleep", level)
 
-    async def wake_up_async(self) -> None:
-        await self.call_utility_async("wake_up")
+    async def wake_up_async(self, tags: Optional[list[str]] = None) -> None:
+        await self.call_utility_async("wake_up", tags)
 
     async def is_sleeping_async(self) -> bool:
         return await self.call_utility_async("is_sleeping")

vllm/v1/engine/llm_engine.py

@@ -245,8 +245,8 @@ class LLMEngine:
     def sleep(self, level: int = 1):
         self.engine_core.sleep(level)
 
-    def wake_up(self):
-        self.engine_core.wake_up()
+    def wake_up(self, tags: Optional[list[str]] = None):
+        self.engine_core.wake_up(tags)
 
     def is_sleeping(self) -> bool:
         return self.engine_core.is_sleeping()

vllm/v1/worker/gpu_worker.py

@@ -83,9 +83,9 @@ class Worker(WorkerBase):
             "%.2f GiB memory is still in use.", freed_bytes / GiB_bytes,
             used_bytes / GiB_bytes)
 
-    def wake_up(self) -> None:
+    def wake_up(self, tags: Optional[list[str]] = None) -> None:
         allocator = CuMemAllocator.get_instance()
-        allocator.wake_up()
+        allocator.wake_up(tags)
 
     def init_device(self):
         if self.device_config.device.type == "cuda":

vllm/worker/worker.py

@@ -135,9 +135,9 @@ class Worker(LocalOrDistributedWorkerBase):
             "%.2f GiB memory is still in use.", freed_bytes / GiB_bytes,
             used_bytes / GiB_bytes)
 
-    def wake_up(self) -> None:
+    def wake_up(self, tags: Optional[list[str]] = None) -> None:
         allocator = CuMemAllocator.get_instance()
-        allocator.wake_up()
+        allocator.wake_up(tags=tags)
 
     def init_device(self) -> None:
         if self.device_config.device.type == "cuda":