python distutils可以編譯出CUDA代碼嗎？

Question

我有 CUDA 代碼，我想使用 distutils 為 Python 構建一個動態庫。 但即使安裝了“nvcc”編譯器，distutils 似乎也無法識別“.cu”文件。 不知道如何完成它。

Answer 1

Distutils 默認無法編譯 CUDA，因為它不支持同時使用多個編譯器。 默認情況下，它會根據您的平台設置為編譯器，而不是您擁有的源代碼類型。

我在 github 上有一個示例項目，其中包含一些猴子補丁到 distutils 中以破解以支持這一點。 示例項目是一個 C++ class，它管理一些 GPU memory 和一個 CUDA kernel，包裝在 swig 中，所有編譯僅使用python setup.py install 重點是數組操作，因此我們也使用 numpy。kernel 對這個示例項目所做的所有操作都是將數組中的每個元素遞增 1。

代碼在這里： https://github.com/rmcgibbo/npcuda-example 。 這是 setup.py 腳本。 整個代碼的關鍵是customize_compiler_for_nvcc() 。

import  os
from os.path import join as pjoin
from setuptools import setup
from distutils.extension import Extension
from distutils.command.build_ext import build_ext
import subprocess
import numpy

def find_in_path(name, path):
    "Find a file in a search path"
    #adapted fom http://code.activestate.com/recipes/52224-find-a-file-given-a-search-path/
    for dir in path.split(os.pathsep):
        binpath = pjoin(dir, name)
        if os.path.exists(binpath):
            return os.path.abspath(binpath)
    return None


def locate_cuda():
    """Locate the CUDA environment on the system

    Returns a dict with keys 'home', 'nvcc', 'include', and 'lib64'
    and values giving the absolute path to each directory.

    Starts by looking for the CUDAHOME env variable. If not found, everything
    is based on finding 'nvcc' in the PATH.
    """

    # first check if the CUDAHOME env variable is in use
    if 'CUDAHOME' in os.environ:
        home = os.environ['CUDAHOME']
        nvcc = pjoin(home, 'bin', 'nvcc')
    else:
        # otherwise, search the PATH for NVCC
        nvcc = find_in_path('nvcc', os.environ['PATH'])
        if nvcc is None:
            raise EnvironmentError('The nvcc binary could not be '
                'located in your $PATH. Either add it to your path, or set $CUDAHOME')
        home = os.path.dirname(os.path.dirname(nvcc))

    cudaconfig = {'home':home, 'nvcc':nvcc,
                  'include': pjoin(home, 'include'),
                  'lib64': pjoin(home, 'lib64')}
    for k, v in cudaconfig.iteritems():
        if not os.path.exists(v):
            raise EnvironmentError('The CUDA %s path could not be located in %s' % (k, v))

    return cudaconfig
CUDA = locate_cuda()


# Obtain the numpy include directory.  This logic works across numpy versions.
try:
    numpy_include = numpy.get_include()
except AttributeError:
    numpy_include = numpy.get_numpy_include()


ext = Extension('_gpuadder',
                sources=['src/swig_wrap.cpp', 'src/manager.cu'],
                library_dirs=[CUDA['lib64']],
                libraries=['cudart'],
                runtime_library_dirs=[CUDA['lib64']],
                # this syntax is specific to this build system
                # we're only going to use certain compiler args with nvcc and not with gcc
                # the implementation of this trick is in customize_compiler() below
                extra_compile_args={'gcc': [],
                                    'nvcc': ['-arch=sm_20', '--ptxas-options=-v', '-c', '--compiler-options', "'-fPIC'"]},
                include_dirs = [numpy_include, CUDA['include'], 'src'])


# check for swig
if find_in_path('swig', os.environ['PATH']):
    subprocess.check_call('swig -python -c++ -o src/swig_wrap.cpp src/swig.i', shell=True)
else:
    raise EnvironmentError('the swig executable was not found in your PATH')



def customize_compiler_for_nvcc(self):
    """inject deep into distutils to customize how the dispatch
    to gcc/nvcc works.

    If you subclass UnixCCompiler, it's not trivial to get your subclass
    injected in, and still have the right customizations (i.e.
    distutils.sysconfig.customize_compiler) run on it. So instead of going
    the OO route, I have this. Note, it's kindof like a wierd functional
    subclassing going on."""

    # tell the compiler it can processes .cu
    self.src_extensions.append('.cu')

    # save references to the default compiler_so and _comple methods
    default_compiler_so = self.compiler_so
    super = self._compile

    # now redefine the _compile method. This gets executed for each
    # object but distutils doesn't have the ability to change compilers
    # based on source extension: we add it.
    def _compile(obj, src, ext, cc_args, extra_postargs, pp_opts):
        if os.path.splitext(src)[1] == '.cu':
            # use the cuda for .cu files
            self.set_executable('compiler_so', CUDA['nvcc'])
            # use only a subset of the extra_postargs, which are 1-1 translated
            # from the extra_compile_args in the Extension class
            postargs = extra_postargs['nvcc']
        else:
            postargs = extra_postargs['gcc']

        super(obj, src, ext, cc_args, postargs, pp_opts)
        # reset the default compiler_so, which we might have changed for cuda
        self.compiler_so = default_compiler_so

    # inject our redefined _compile method into the class
    self._compile = _compile


# run the customize_compiler
class custom_build_ext(build_ext):
    def build_extensions(self):
        customize_compiler_for_nvcc(self.compiler)
        build_ext.build_extensions(self)

setup(name='gpuadder',
      # random metadata. there's more you can supploy
      author='Robert McGibbon',
      version='0.1',

      # this is necessary so that the swigged python file gets picked up
      py_modules=['gpuadder'],
      package_dir={'': 'src'},

      ext_modules = [ext],

      # inject our custom trigger
      cmdclass={'build_ext': custom_build_ext},

      # since the package has c code, the egg cannot be zipped
      zip_safe=False)

Answer 2

作為distutils / setuptools的替代方案，您可以使用scikit-build （連同CMakeLists.txt 、 pyproject.toml和setup.cfg / setup.py ）：

import sys
from pathlib import Path
from skbuild import setup
from setuptools import find_packages

# https://github.com/scikit-build/scikit-build/issues/521#issuecomment-753035688
for i in (Path(__file__).resolve().parent / "_skbuild").rglob("CMakeCache.txt"):
    i.write_text(re.sub("^//.*$\n^[^#].*pip-build-env.*$", "", i.read_text(), flags=re.M))

setup(cmake_args=[f"-DPython3_ROOT_DIR={sys.prefix}"],
      packages=find_packages(exclude=["tests"]))