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enginex-c_series-vllm/distributed/device_communicators/cuda_wrapper.py

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2025-08-13 19:46:19 +08:00
# SPDX-License-Identifier: Apache-2.0
# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
"""This file is a pure Python wrapper for the cudart library.
It avoids the need to compile a separate shared library, and is
convenient for use when we just need to call a few functions.
"""
import ctypes
from dataclasses import dataclass
from typing import Any, Optional
# this line makes it possible to directly load `libcudart.so` using `ctypes`
import torch # noqa
import vllm.envs as envs
from vllm.logger import init_logger
logger = init_logger(__name__)
# === export types and functions from cudart to Python ===
# for the original cudart definition, please check
# https://docs.nvidia.com/cuda/cuda-runtime-api/index.html
cudaError_t = ctypes.c_int
cudaMemcpyKind = ctypes.c_int
class cudaIpcMemHandle_t(ctypes.Structure):
_fields_ = [("internal", ctypes.c_byte * 128)]
@dataclass
class Function:
name: str
restype: Any
argtypes: list[Any]
def find_loaded_library(lib_name) -> Optional[str]:
"""
According to according to https://man7.org/linux/man-pages/man5/proc_pid_maps.5.html,
the file `/proc/self/maps` contains the memory maps of the process, which includes the
shared libraries loaded by the process. We can use this file to find the path of the
a loaded library.
""" # noqa
found = False
with open("/proc/self/maps") as f:
for line in f:
if lib_name in line:
found = True
break
if not found:
# the library is not loaded in the current process
return None
# if lib_name is libcudart, we need to match a line with:
# address /path/to/libcudart-hash.so.11.0
start = line.index("/")
path = line[start:].strip()
filename = path.split("/")[-1]
assert filename.rpartition(".so")[0].startswith(lib_name), \
f"Unexpected filename: {filename} for library {lib_name}"
return path
class CudaRTLibrary:
exported_functions = [
# cudaError_t cudaSetDevice ( int device )
Function("mcSetDevice", cudaError_t, [ctypes.c_int]),
# cudaError_t cudaDeviceSynchronize ( void )
Function("mcDeviceSynchronize", cudaError_t, []),
# cudaError_t cudaDeviceReset ( void )
Function("mcDeviceReset", cudaError_t, []),
# const char* cudaGetErrorString ( cudaError_t error )
Function("mcGetErrorString", ctypes.c_char_p, [cudaError_t]),
# cudaError_t cudaMalloc ( void** devPtr, size_t size )
Function("mcMalloc", cudaError_t,
[ctypes.POINTER(ctypes.c_void_p), ctypes.c_size_t]),
# cudaError_t cudaFree ( void* devPtr )
Function("mcFree", cudaError_t, [ctypes.c_void_p]),
# cudaError_t cudaMemset ( void* devPtr, int value, size_t count )
Function("mcMemset", cudaError_t,
[ctypes.c_void_p, ctypes.c_int, ctypes.c_size_t]),
# cudaError_t cudaMemcpy ( void* dst, const void* src, size_t count, cudaMemcpyKind kind ) # noqa
Function("mcMemcpy", cudaError_t, [
ctypes.c_void_p, ctypes.c_void_p, ctypes.c_size_t, cudaMemcpyKind
]),
# cudaError_t cudaIpcGetMemHandle ( cudaIpcMemHandle_t* handle, void* devPtr ) # noqa
Function("mcIpcGetMemHandle", cudaError_t,
[ctypes.POINTER(cudaIpcMemHandle_t), ctypes.c_void_p]),
# cudaError_t cudaIpcOpenMemHandle ( void** devPtr, cudaIpcMemHandle_t handle, unsigned int flags ) # noqa
Function("mcIpcOpenMemHandle", cudaError_t, [
ctypes.POINTER(ctypes.c_void_p), cudaIpcMemHandle_t, ctypes.c_uint
]),
]
# class attribute to store the mapping from the path to the library
# to avoid loading the same library multiple times
path_to_library_cache: dict[str, Any] = {}
# class attribute to store the mapping from library path
# to the corresponding dictionary
path_to_dict_mapping: dict[str, dict[str, Any]] = {}
def __init__(self, so_file: Optional[str] = None):
if so_file is None:
so_file = find_loaded_library("libmcruntime")
if so_file is None:
so_file = envs.VLLM_CUDART_SO_PATH # fallback to env var
assert so_file is not None, \
(
"libcudart is not loaded in the current process, "
"try setting VLLM_CUDART_SO_PATH"
)
if so_file not in CudaRTLibrary.path_to_library_cache:
lib = ctypes.CDLL(so_file)
CudaRTLibrary.path_to_library_cache[so_file] = lib
self.lib = CudaRTLibrary.path_to_library_cache[so_file]
if so_file not in CudaRTLibrary.path_to_dict_mapping:
_funcs = {}
for func in CudaRTLibrary.exported_functions:
f = getattr(self.lib, func.name)
f.restype = func.restype
f.argtypes = func.argtypes
_funcs[func.name] = f
CudaRTLibrary.path_to_dict_mapping[so_file] = _funcs
self.funcs = CudaRTLibrary.path_to_dict_mapping[so_file]
def CUDART_CHECK(self, result: cudaError_t) -> None:
if result != 0:
error_str = self.cudaGetErrorString(result)
raise RuntimeError(f"CUDART error: {error_str}")
def cudaGetErrorString(self, error: cudaError_t) -> str:
return self.funcs["mcGetErrorString"](error).decode("utf-8")
def cudaSetDevice(self, device: int) -> None:
self.CUDART_CHECK(self.funcs["mcSetDevice"](device))
def cudaDeviceSynchronize(self) -> None:
self.CUDART_CHECK(self.funcs["mcDeviceSynchronize"]())
def cudaDeviceReset(self) -> None:
self.CUDART_CHECK(self.funcs["mcDeviceReset"]())
def cudaMalloc(self, size: int) -> ctypes.c_void_p:
devPtr = ctypes.c_void_p()
self.CUDART_CHECK(self.funcs["mcMalloc"](ctypes.byref(devPtr), size))
return devPtr
def cudaFree(self, devPtr: ctypes.c_void_p) -> None:
self.CUDART_CHECK(self.funcs["mcFree"](devPtr))
def cudaMemset(self, devPtr: ctypes.c_void_p, value: int,
count: int) -> None:
self.CUDART_CHECK(self.funcs["mcMemset"](devPtr, value, count))
def cudaMemcpy(self, dst: ctypes.c_void_p, src: ctypes.c_void_p,
count: int) -> None:
cudaMemcpyDefault = 4
kind = cudaMemcpyDefault
self.CUDART_CHECK(self.funcs["mcMemcpy"](dst, src, count, kind))
def cudaIpcGetMemHandle(self,
devPtr: ctypes.c_void_p) -> cudaIpcMemHandle_t:
handle = cudaIpcMemHandle_t()
self.CUDART_CHECK(self.funcs["mcIpcGetMemHandle"](
ctypes.byref(handle), devPtr))
return handle
def cudaIpcOpenMemHandle(self,
handle: cudaIpcMemHandle_t) -> ctypes.c_void_p:
cudaIpcMemLazyEnablePeerAccess = 1
devPtr = ctypes.c_void_p()
self.CUDART_CHECK(self.funcs["mcIpcOpenMemHandle"](
ctypes.byref(devPtr), handle, cudaIpcMemLazyEnablePeerAccess))
return devPtr