eacbb73968
Before this commit, the benchmarking infrastructure used heterogeneous protocols between library (e.g., CUTLASS uses a C++ binary that reports mean TFLOPS; torch and triton use python call and report 10th, 50th and 90th quantiles). For the sake of uniformity and fair benchmark practices, this PR adds a python wrapper for auto-tuned CUTLASS matrix multiplication. Benchmarks have been rewritten to use this wrapper with `triton.testing.do_bench` rather than system calls to CUTLASS profiler. Importantly, this also ensures that all the matmuls are done on the *same* input data which should stabilize clock across providers.
130 lines
5.0 KiB
Python
130 lines
5.0 KiB
Python
import os
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import re
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import sys
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import sysconfig
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import platform
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import subprocess
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import distutils
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import glob
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from distutils.version import LooseVersion
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from setuptools import setup, Extension, find_packages
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from torch.utils.cpp_extension import include_paths, library_paths
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from setuptools.command.build_ext import build_ext
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from setuptools.command.test import test as TestCommand
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import distutils.spawn
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import torch
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def find_llvm():
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versions = ["-10", "-10.0", ""]
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supported = ["llvm-config{v}".format(v=v) for v in versions]
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paths = [distutils.spawn.find_executable(cfg) for cfg in supported]
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paths = [p for p in paths if p is not None]
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if paths:
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return paths[0]
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config = distutils.spawn.find_executable("llvm-config")
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instructions = "Please install llvm-10-dev"
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if config is None:
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raise RuntimeError("Could not find llvm-config. " + instructions)
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version = os.popen("{config} --version".format(config=config)).read()
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raise RuntimeError("Version {v} not supported. ".format(v=version) + instructions)
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class CMakeExtension(Extension):
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def __init__(self, name, path, sourcedir=""):
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Extension.__init__(self, name, sources=[])
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self.sourcedir = os.path.abspath(sourcedir)
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self.path = path
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class CMakeBuild(build_ext):
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def run(self):
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try:
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out = subprocess.check_output(["cmake", "--version"])
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except OSError:
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raise RuntimeError(
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"CMake must be installed to build the following extensions: " +
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", ".join(e.name for e in self.extensions)
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)
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if platform.system() == "Windows":
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cmake_version = LooseVersion(re.search(r"version\s*([\d.]+)", out.decode()).group(1))
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if cmake_version < "3.1.0":
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raise RuntimeError("CMake >= 3.1.0 is required on Windows")
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for ext in self.extensions:
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self.build_extension(ext)
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def build_extension(self, ext):
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# self.debug = True
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self.debug = False
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extdir = os.path.abspath(os.path.dirname(self.get_ext_fullpath(ext.path)))
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# python directories
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python_include_dirs = distutils.sysconfig.get_python_inc()
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python_lib_dirs = distutils.sysconfig.get_config_var("LIBDIR")
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torch_include_dirs = include_paths(True)
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torch_library_dirs = library_paths(True)
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cxx11abi = str(int(torch._C._GLIBCXX_USE_CXX11_ABI))
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cmake_args = [
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"-DCMAKE_LIBRARY_OUTPUT_DIRECTORY=" + extdir,
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"-DBUILD_TUTORIALS=OFF",
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"-DBUILD_PYTHON_MODULE=ON",
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#'-DPYTHON_EXECUTABLE=' + sys.executable,
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#'-DCMAKE_VERBOSE_MAKEFILE:BOOL=ON,
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"-DPYTHON_INCLUDE_DIRS=" + ";".join([python_include_dirs] + include_paths(True)),
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"-DPYTHON_LINK_DIRS=" + ";".join(library_paths(True)),
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"-DTORCH_CXX11_ABI=" + cxx11abi,
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"-DTORCH_LIBRARIES=c10;c10_cuda;torch;torch_cuda;torch_cpu;torch_python;triton",
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"-DLLVM_CONFIG=" + find_llvm(),
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]
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# configuration
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cfg = "Debug" if self.debug else "Release"
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build_args = ["--config", cfg]
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if platform.system() == "Windows":
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cmake_args += ["-DCMAKE_LIBRARY_OUTPUT_DIRECTORY_{}={}".format(cfg.upper(), extdir)]
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if sys.maxsize > 2**32:
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cmake_args += ["-A", "x64"]
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build_args += ["--", "/m"]
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else:
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cmake_args += ["-DCMAKE_BUILD_TYPE=" + cfg]
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build_args += ["--", "-j4"]
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env = os.environ.copy()
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if not os.path.exists(self.build_temp):
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os.makedirs(self.build_temp)
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sourcedir = os.path.abspath(os.path.join(os.path.dirname(__file__), "src"))
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subprocess.check_call(["cmake", sourcedir] + cmake_args, cwd=self.build_temp, env=env)
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subprocess.check_call(["cmake", "--build", "."] + build_args, cwd=self.build_temp)
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setup(
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name="triton",
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version="1.0.0",
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author="Philippe Tillet",
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author_email="phil@openai.com",
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description="A language and compiler for custom Deep Learning operations",
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long_description="",
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packages=["triton", "triton/_C", "triton/ops", "triton/ops/blocksparse"],
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install_requires=["numpy", "torch"],
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package_data={
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"triton/ops": ["*.c"],
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"triton/ops/blocksparse": ["*.c"]
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},
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include_package_data=True,
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ext_modules=[CMakeExtension("triton", "triton/_C/")],
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cmdclass={"build_ext": CMakeBuild},
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zip_safe=False,
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# for PyPI
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keywords=["Compiler", "Deep Learning"],
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url="https://github.com/ptillet/triton/",
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download_url="https://github.com/ptillet/triton/archive/v0.1.tar.gz",
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classifiers=[
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"Development Status :: 3 - Alpha", # Chose either "3 - Alpha", "4 - Beta" or "5 - Production/Stable" as the current state of your package
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"Intended Audience :: Developers", # Define that your audience are developers
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"Topic :: Software Development :: Build Tools",
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"License :: OSI Approved :: MIT License", # Again, pick a license
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"Programming Language :: Python :: 3.6",
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],
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)
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