vllm.utils.numa_utils ¶

def _can_set_mempolicy() -> bool:
    """Check whether the current process can use NUMA memory policy syscalls."""
    try:
        libnuma = get_libnuma()
        if libnuma is None or libnuma.numa_available() < 0:
            return False
        mode = ctypes.c_int()
        ret = libnuma.get_mempolicy(
            ctypes.byref(mode), None, ctypes.c_ulong(0), None, ctypes.c_ulong(0)
        )
        return ret == 0
    except Exception:
        return False

def _get_gpu_index(
    parallel_config, local_rank: int, dp_local_rank: int | None = None
) -> int:
    """Compute the physical GPU index used for NUMA lookup."""
    if (
        parallel_config.distributed_executor_backend not in ("ray", "external_launcher")
        and parallel_config.data_parallel_backend != "ray"
        and parallel_config.nnodes_within_dp == 1
    ):
        if dp_local_rank is None:
            dp_local_rank = parallel_config.data_parallel_rank_local
            if dp_local_rank is None:
                dp_local_rank = parallel_config.data_parallel_index

        tp_pp_world_size = (
            parallel_config.pipeline_parallel_size
            * parallel_config.tensor_parallel_size
        )
        return local_rank + dp_local_rank * tp_pp_world_size

    return local_rank

def _get_numactl_executable() -> tuple[str, str]:
    """Return the fixed wrapper executable used to launch numactl."""
    from shutil import which

    if which("numactl") is None:
        raise RuntimeError(
            "numactl is required for NUMA binding but is not installed or "
            "not available on PATH."
        )

    script_path = Path(__file__).with_name("numa_wrapper.sh")
    return str(script_path), f"{script_path} via {_NUMACTL_ARGS_ENV}"

def _is_auto_numa_available() -> bool:
    """Check whether automatic GPU-to-NUMA detection should be attempted."""
    from vllm.platforms import current_platform

    if not current_platform.is_cuda_alike():
        return False

    if not os.path.isdir("/sys/devices/system/node/node1"):
        return False

    try:
        process = psutil.Process(os.getpid())
        cpu_affinity = process.cpu_affinity()
        cpu_count = psutil.cpu_count()
        if cpu_count is not None and cpu_affinity != list(range(cpu_count)):
            logger.warning(
                "CPU affinity is already constrained for this process. "
                "Skipping automatic NUMA binding; pass --numa-bind-nodes "
                "explicitly to override."
            )
            return False
    except (AttributeError, NotImplementedError, psutil.Error):
        pass

    if not _can_set_mempolicy():
        logger.warning(
            "User lacks permission to set NUMA memory policy. "
            "Automatic NUMA detection may not work; if you are using Docker, "
            "try adding --cap-add SYS_NICE."
        )
        return False

    if not hasattr(current_platform, "get_all_device_numa_nodes"):
        logger.warning(
            "Platform %s does not support automatic NUMA detection",
            type(current_platform).__name__,
        )
        return False

    return True

@contextmanager
def configure_subprocess(
    vllm_config: "VllmConfig",
    local_rank: int,
    dp_local_rank: int | None = None,
    process_kind: str = "worker",
):
    """Temporarily replace the multiprocessing executable with a numactl wrapper."""
    numactl_args = _get_numactl_args(
        vllm_config, local_rank, dp_local_rank, process_kind
    )
    if numactl_args is None:
        yield
        return

    executable, debug_str = _get_numactl_executable()
    python_executable = os.fsdecode(multiprocessing.spawn.get_executable())
    with (
        _set_numa_wrapper_env(numactl_args, python_executable),
        _mp_set_executable(executable, debug_str),
    ):
        yield

@cache
def get_auto_numa_nodes() -> list[int] | None:
    """Auto-detect NUMA nodes for all visible GPUs."""
    from vllm.platforms import current_platform

    if not _is_auto_numa_available():
        return None

    numa_nodes = current_platform.get_all_device_numa_nodes()
    if numa_nodes is not None:
        logger.info("Auto-detected NUMA nodes for GPUs: %s", numa_nodes)
    return numa_nodes

def log_current_affinity_state(label: str) -> None:
    """Log the process's effective NUMA affinity state."""
    _log_numactl_show(label)