Sync from v0.13

2026-01-19 10:38:50 +08:00
parent b2ef04d792
commit 5aef6c175a
3714 changed files with 854317 additions and 89342 deletions
--- a/tests/distributed/test_nccl_symm_mem_allreduce.py
+++ b/tests/distributed/test_nccl_symm_mem_allreduce.py
@@ -0,0 +1,94 @@
+# SPDX-License-Identifier: Apache-2.0
+# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
+
+import random
+import typing
+
+import pytest
+import torch
+import torch.distributed as dist
+import torch.multiprocessing as mp
+
+import vllm.envs as envs
+from vllm.distributed import cleanup_dist_env_and_memory
+from vllm.distributed.device_communicators.cuda_communicator import CudaCommunicator
+from vllm.distributed.device_communicators.pynccl import register_nccl_symmetric_ops
+from vllm.distributed.device_communicators.pynccl_allocator import (
+    get_nccl_mem_pool,
+    is_symmetric_memory_enabled,
+)
+from vllm.distributed.parallel_state import (
+    get_tp_group,
+    init_distributed_environment,
+    initialize_model_parallel,
+)
+from vllm.platforms import current_platform
+from vllm.utils.system_utils import update_environment_variables
+
+torch.manual_seed(42)
+random.seed(44)
+
+test_size_elements = 4 * 1024 * 1024
+
+
+def nccl_symm_mem_allreduce_worker(local_rank: int, world_size: int):
+    monkeypatch = pytest.MonkeyPatch()
+    with monkeypatch.context() as m:
+        m.delenv("CUDA_VISIBLE_DEVICES", raising=False)
+        dtype = torch.bfloat16
+        device = torch.device(f"cuda:{local_rank}")
+        torch.cuda.set_device(device)
+        torch.set_default_device(device)
+        torch.set_default_dtype(dtype)
+        update_environment_variables(
+            {
+                "RANK": str(local_rank),
+                "LOCAL_RANK": str(local_rank),
+                "WORLD_SIZE": str(world_size),
+                "MASTER_ADDR": "localhost",
+                "MASTER_PORT": "12345",
+            }
+        )
+
+        init_distributed_environment()
+        initialize_model_parallel(tensor_model_parallel_size=world_size)
+
+        cuda_communicator = typing.cast(
+            CudaCommunicator, get_tp_group().device_communicator
+        )
+        pynccl_comm = cuda_communicator.pynccl_comm
+        if get_nccl_mem_pool() is None:
+            pytest.skip(
+                "NCCL allocator compilation failed (probably missing NCCL headers)."
+            )
+        if not is_symmetric_memory_enabled():
+            pytest.skip("NCCL symmetric memory allreduce is disabled.")
+
+        register_nccl_symmetric_ops(pynccl_comm)
+        input = torch.randint(1, 23, (test_size_elements,), dtype=dtype, device=device)
+        input_clone = input.clone()
+        output = torch.ops.vllm.all_reduce_symmetric_with_copy(input)
+        assert output is not None
+
+        group = get_tp_group().device_group
+        dist.all_reduce(input_clone, group=group)
+        torch.testing.assert_close(output, input_clone, atol=2.5, rtol=0.1)
+
+
+@pytest.mark.skipif(
+    not current_platform.is_cuda(),
+    reason="NCCLSymmMemAllreduce is only available for CUDA platforms.",
+)
+@pytest.mark.parametrize("world_size", [2])
+@pytest.mark.skipif(envs.VLLM_TARGET_DEVICE not in ["cuda"], reason="Only test on CUDA")
+def test_nccl_symm_mem_allreduce(monkeypatch: pytest.MonkeyPatch, world_size):
+    if world_size > torch.cuda.device_count():
+        pytest.skip("Not enough GPUs to run the test.")
+
+    # Enable SymmMemCommunicator
+    monkeypatch.setenv("VLLM_USE_NCCL_SYMM_MEM", "1")
+    monkeypatch.setenv("NCCL_NVLS_ENABLE", "1")
+    monkeypatch.setenv("NCCL_CUMEM_ENABLE", "1")
+
+    mp.spawn(nccl_symm_mem_allreduce_worker, args=(world_size,), nprocs=world_size)
+    cleanup_dist_env_and_memory()