[Core] nccl integrity check and test (vllm-project#4155)

[Core] Add integrity check during initialization; add test for it (vllm-project#4155)

.buildkite/test-pipeline.yaml

@@ -33,6 +33,7 @@ steps:
   num_gpus: 2 # only support 1 or 2 for now.
   commands:
   - pytest -v -s test_pynccl.py
+  - pytest -v -s test_pynccl_library.py
   - TEST_DIST_MODEL=facebook/opt-125m pytest -v -s test_basic_distributed_correctness.py
   - TEST_DIST_MODEL=meta-llama/Llama-2-7b-hf pytest -v -s test_basic_distributed_correctness.py
   - TEST_DIST_MODEL=facebook/opt-125m pytest -v -s test_chunked_prefill_distributed.py

tests/distributed/test_pynccl_library.py

@@ -0,0 +1,43 @@
+import multiprocessing
+import tempfile
+
+
+def target_fn(env, filepath):
+    from vllm.utils import update_environment_variables
+    update_environment_variables(env)
+    from vllm.utils import nccl_integrity_check
+    nccl_integrity_check(filepath)
+
+
+def test_library_file():
+    # note: don't import vllm.distributed.device_communicators.pynccl
+    # before running this test, otherwise the library file will be loaded
+    # and it might interfere with the test
+    from vllm.utils import find_nccl_library
+    so_file = find_nccl_library()
+    with open(so_file, 'rb') as f:
+        content = f.read()
+    try:
+        # corrupt the library file, should raise an exception
+        with open(so_file, 'wb') as f:
+            f.write(content[:len(content) // 2])
+        p = multiprocessing.Process(target=target_fn, args=({}, so_file))
+        p.start()
+        p.join()
+        assert p.exitcode != 0
+
+        # move the library file to a tmp path
+        # test VLLM_NCCL_SO_PATH
+        fd, path = tempfile.mkstemp()
+        with open(path, 'wb') as f:
+            f.write(content)
+        p = multiprocessing.Process(target=target_fn,
+                                    args=({
+                                        "VLLM_NCCL_SO_PATH": path
+                                    }, path))
+        p.start()
+        p.join()
+        assert p.exitcode == 0
+    finally:
+        with open(so_file, 'wb') as f:
+            f.write(content)

vllm/distributed/device_communicators/pynccl.py

@@ -21,49 +21,35 @@
 
 import ctypes
 import datetime
-import glob
-import os
+import platform
 
 # ===================== import region =====================
 import torch
 import torch.distributed as dist
 from torch.distributed import ReduceOp
 
 from vllm.logger import init_logger
+from vllm.utils import find_nccl_library, nccl_integrity_check
 
 logger = init_logger(__name__)
 
-so_file = os.environ.get("VLLM_NCCL_SO_PATH", "")
-
-# check if we have vllm-managed nccl
-vllm_nccl_path = None
-if torch.version.cuda is not None:
-    cuda_major = torch.version.cuda.split(".")[0]
-    path = os.path.expanduser(
-        f"~/.config/vllm/nccl/cu{cuda_major}/libnccl.so.*")
-    files = glob.glob(path)
-    vllm_nccl_path = files[0] if files else None
-
-# manually load the nccl library
-if so_file:
-    logger.info(
-        f"Loading nccl from environment variable VLLM_NCCL_SO_PATH={so_file}")
-else:
-    if torch.version.cuda is not None:
-        so_file = vllm_nccl_path or "libnccl.so.2"
-    elif torch.version.hip is not None:
-        so_file = "librccl.so.1"
-    else:
-        raise ValueError("NCCL only supports CUDA and ROCm backends.")
-    logger.info(f"Loading nccl from library {so_file}")
+so_file = find_nccl_library()
 
 try:
+    # load the library in another process.
+    # if it core dumps, it will not crash the current process
+    nccl_integrity_check(so_file)
     nccl = ctypes.CDLL(so_file)
 except Exception as e:
     logger.error(
         f"Failed to load NCCL library from {so_file} ."
         "It is expected if you are not running on NVIDIA/AMD GPUs."
-        "Otherwise please set the environment variable VLLM_NCCL_SO_PATH"
+        "Otherwise, the nccl library might not exist, be corrupted "
+        f"or it does not support the current platform {platform.platform()}."
+        f"One solution is to download libnccl2 version 2.18 from "
+        f"https://developer.download.nvidia.com/compute/cuda/repos/ "
+        f"and extract the libnccl.so.2 file. If you already have the "
+        f"library, please set the environment variable VLLM_NCCL_SO_PATH"
         " to point to the correct nccl library path.")
     raise e
 

vllm/utils.py

@@ -1,6 +1,7 @@
 import asyncio
 import enum
 import gc
+import glob
 import os
 import socket
 import subprocess
@@ -517,3 +518,53 @@ def init_cached_hf_modules():
     """
     from transformers.dynamic_module_utils import init_hf_modules
     init_hf_modules()
+
+
+def nccl_integrity_check(filepath):
+    """
+    when the library is corrupted, we cannot catch
+    the exception in python. it will crash the process.
+    instead, we use the exit code of `ldd` to check
+    if the library is corrupted. if not, we will return
+    the version of the library.
+    """
+    exit_code = os.system(f"ldd {filepath} 2>&1 > /dev/null")
+    if exit_code != 0:
+        raise RuntimeError(f"Failed to load NCCL library from {filepath} .")
+    import ctypes
+
+    nccl = ctypes.CDLL(filepath)
+    version = ctypes.c_int()
+    nccl.ncclGetVersion.restype = ctypes.c_int
+    nccl.ncclGetVersion.argtypes = [ctypes.POINTER(ctypes.c_int)]
+    result = nccl.ncclGetVersion(ctypes.byref(version))
+    assert result == 0
+    return version.value
+
+
+def find_nccl_library():
+    so_file = os.environ.get("VLLM_NCCL_SO_PATH", "")
+
+    # check if we have vllm-managed nccl
+    vllm_nccl_path = None
+    if torch.version.cuda is not None:
+        cuda_major = torch.version.cuda.split(".")[0]
+        path = os.path.expanduser(
+            f"~/.config/vllm/nccl/cu{cuda_major}/libnccl.so.*")
+        files = glob.glob(path)
+        vllm_nccl_path = files[0] if files else None
+
+    # manually load the nccl library
+    if so_file:
+        logger.info(
+            f"Found nccl from environment variable VLLM_NCCL_SO_PATH={so_file}"
+        )
+    else:
+        if torch.version.cuda is not None:
+            so_file = vllm_nccl_path or "libnccl.so.2"
+        elif torch.version.hip is not None:
+            so_file = "librccl.so.1"
+        else:
+            raise ValueError("NCCL only supports CUDA and ROCm backends.")
+        logger.info(f"Found nccl from library {so_file}")
+    return so_file