# Copyright 2017 The Meson development team # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # http://www.apache.org/licenses/LICENSE-2.0 # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. from __future__ import annotations import typing as T import re from ..mesonlib import version_compare from ..compilers.cuda import CudaCompiler from . import NewExtensionModule, ModuleInfo from ..interpreterbase import ( flatten, permittedKwargs, noKwargs, InvalidArguments ) if T.TYPE_CHECKING: from . import ModuleState from ..compilers import Compiler class CudaModule(NewExtensionModule): INFO = ModuleInfo('CUDA', '0.50.0', unstable=True) def __init__(self, *args, **kwargs): super().__init__() self.methods.update({ "min_driver_version": self.min_driver_version, "nvcc_arch_flags": self.nvcc_arch_flags, "nvcc_arch_readable": self.nvcc_arch_readable, }) @noKwargs def min_driver_version(self, state: 'ModuleState', args: T.Tuple[str], kwargs: T.Dict[str, T.Any]) -> str: argerror = InvalidArguments('min_driver_version must have exactly one positional argument: ' + 'a CUDA Toolkit version string. Beware that, since CUDA 11.0, ' + 'the CUDA Toolkit\'s components (including NVCC) are versioned ' + 'independently from each other (and the CUDA Toolkit as a whole).') if len(args) != 1 or not isinstance(args[0], str): raise argerror cuda_version = args[0] driver_version_table = [ {'cuda_version': '>=11.7.0', 'windows': '516.01', 'linux': '515.43.04'}, {'cuda_version': '>=11.6.1', 'windows': '511.65', 'linux': '510.47.03'}, {'cuda_version': '>=11.6.0', 'windows': '511.23', 'linux': '510.39.01'}, {'cuda_version': '>=11.5.1', 'windows': '496.13', 'linux': '495.29.05'}, {'cuda_version': '>=11.5.0', 'windows': '496.04', 'linux': '495.29.05'}, {'cuda_version': '>=11.4.3', 'windows': '472.50', 'linux': '470.82.01'}, {'cuda_version': '>=11.4.1', 'windows': '471.41', 'linux': '470.57.02'}, {'cuda_version': '>=11.4.0', 'windows': '471.11', 'linux': '470.42.01'}, {'cuda_version': '>=11.3.0', 'windows': '465.89', 'linux': '465.19.01'}, {'cuda_version': '>=11.2.2', 'windows': '461.33', 'linux': '460.32.03'}, {'cuda_version': '>=11.2.1', 'windows': '461.09', 'linux': '460.32.03'}, {'cuda_version': '>=11.2.0', 'windows': '460.82', 'linux': '460.27.03'}, {'cuda_version': '>=11.1.1', 'windows': '456.81', 'linux': '455.32'}, {'cuda_version': '>=11.1.0', 'windows': '456.38', 'linux': '455.23'}, {'cuda_version': '>=11.0.3', 'windows': '451.82', 'linux': '450.51.06'}, {'cuda_version': '>=11.0.2', 'windows': '451.48', 'linux': '450.51.05'}, {'cuda_version': '>=11.0.1', 'windows': '451.22', 'linux': '450.36.06'}, {'cuda_version': '>=10.2.89', 'windows': '441.22', 'linux': '440.33'}, {'cuda_version': '>=10.1.105', 'windows': '418.96', 'linux': '418.39'}, {'cuda_version': '>=10.0.130', 'windows': '411.31', 'linux': '410.48'}, {'cuda_version': '>=9.2.148', 'windows': '398.26', 'linux': '396.37'}, {'cuda_version': '>=9.2.88', 'windows': '397.44', 'linux': '396.26'}, {'cuda_version': '>=9.1.85', 'windows': '391.29', 'linux': '390.46'}, {'cuda_version': '>=9.0.76', 'windows': '385.54', 'linux': '384.81'}, {'cuda_version': '>=8.0.61', 'windows': '376.51', 'linux': '375.26'}, {'cuda_version': '>=8.0.44', 'windows': '369.30', 'linux': '367.48'}, {'cuda_version': '>=7.5.16', 'windows': '353.66', 'linux': '352.31'}, {'cuda_version': '>=7.0.28', 'windows': '347.62', 'linux': '346.46'}, ] driver_version = 'unknown' for d in driver_version_table: if version_compare(cuda_version, d['cuda_version']): driver_version = d.get(state.host_machine.system, d['linux']) break return driver_version @permittedKwargs(['detected']) def nvcc_arch_flags(self, state: 'ModuleState', args: T.Tuple[T.Union[Compiler, CudaCompiler, str]], kwargs: T.Dict[str, T.Any]) -> T.List[str]: nvcc_arch_args = self._validate_nvcc_arch_args(args, kwargs) ret = self._nvcc_arch_flags(*nvcc_arch_args)[0] return ret @permittedKwargs(['detected']) def nvcc_arch_readable(self, state: 'ModuleState', args: T.Tuple[T.Union[Compiler, CudaCompiler, str]], kwargs: T.Dict[str, T.Any]) -> T.List[str]: nvcc_arch_args = self._validate_nvcc_arch_args(args, kwargs) ret = self._nvcc_arch_flags(*nvcc_arch_args)[1] return ret @staticmethod def _break_arch_string(s): s = re.sub('[ \t\r\n,;]+', ';', s) s = s.strip(';').split(';') return s @staticmethod def _detected_cc_from_compiler(c): if isinstance(c, CudaCompiler): return c.detected_cc return '' @staticmethod def _version_from_compiler(c): if isinstance(c, CudaCompiler): return c.version if isinstance(c, str): return c return 'unknown' def _validate_nvcc_arch_args(self, args, kwargs): argerror = InvalidArguments('The first argument must be an NVCC compiler object, or its version string!') if len(args) < 1: raise argerror else: compiler = args[0] cuda_version = self._version_from_compiler(compiler) if cuda_version == 'unknown': raise argerror arch_list = [] if len(args) <= 1 else flatten(args[1:]) arch_list = [self._break_arch_string(a) for a in arch_list] arch_list = flatten(arch_list) if len(arch_list) > 1 and not set(arch_list).isdisjoint({'All', 'Common', 'Auto'}): raise InvalidArguments('''The special architectures 'All', 'Common' and 'Auto' must appear alone, as a positional argument!''') arch_list = arch_list[0] if len(arch_list) == 1 else arch_list detected = kwargs.get('detected', self._detected_cc_from_compiler(compiler)) detected = flatten([detected]) detected = [self._break_arch_string(a) for a in detected] detected = flatten(detected) if not set(detected).isdisjoint({'All', 'Common', 'Auto'}): raise InvalidArguments('''The special architectures 'All', 'Common' and 'Auto' must appear alone, as a positional argument!''') return cuda_version, arch_list, detected def _filter_cuda_arch_list(self, cuda_arch_list, lo=None, hi=None, saturate=None): """ Filter CUDA arch list (no codenames) for >= low and < hi architecture bounds, and deduplicate. If saturate is provided, architectures >= hi are replaced with saturate. """ filtered_cuda_arch_list = [] for arch in cuda_arch_list: if arch: if lo and version_compare(arch, '<' + lo): continue if hi and version_compare(arch, '>=' + hi): if not saturate: continue arch = saturate if arch not in filtered_cuda_arch_list: filtered_cuda_arch_list.append(arch) return filtered_cuda_arch_list def _nvcc_arch_flags(self, cuda_version, cuda_arch_list='Auto', detected=''): """ Using the CUDA Toolkit version and the target architectures, compute the NVCC architecture flags. """ # Replicates much of the logic of # https://github.com/Kitware/CMake/blob/master/Modules/FindCUDA/select_compute_arch.cmake # except that a bug with cuda_arch_list="All" is worked around by # tracking both lower and upper limits on GPU architectures. cuda_known_gpu_architectures = ['Fermi', 'Kepler', 'Maxwell'] # noqa: E221 cuda_common_gpu_architectures = ['3.0', '3.5', '5.0'] # noqa: E221 cuda_hi_limit_gpu_architecture = None # noqa: E221 cuda_lo_limit_gpu_architecture = '2.0' # noqa: E221 cuda_all_gpu_architectures = ['3.0', '3.2', '3.5', '5.0'] # noqa: E221 if version_compare(cuda_version, '<7.0'): cuda_hi_limit_gpu_architecture = '5.2' if version_compare(cuda_version, '>=7.0'): cuda_known_gpu_architectures += ['Kepler+Tegra', 'Kepler+Tesla', 'Maxwell+Tegra'] # noqa: E221 cuda_common_gpu_architectures += ['5.2'] # noqa: E221 if version_compare(cuda_version, '<8.0'): cuda_common_gpu_architectures += ['5.2+PTX'] # noqa: E221 cuda_hi_limit_gpu_architecture = '6.0' # noqa: E221 if version_compare(cuda_version, '>=8.0'): cuda_known_gpu_architectures += ['Pascal', 'Pascal+Tegra'] # noqa: E221 cuda_common_gpu_architectures += ['6.0', '6.1'] # noqa: E221 cuda_all_gpu_architectures += ['6.0', '6.1', '6.2'] # noqa: E221 if version_compare(cuda_version, '<9.0'): cuda_common_gpu_architectures += ['6.1+PTX'] # noqa: E221 cuda_hi_limit_gpu_architecture = '7.0' # noqa: E221 if version_compare(cuda_version, '>=9.0'): cuda_known_gpu_architectures += ['Volta', 'Xavier'] # noqa: E221 cuda_common_gpu_architectures += ['7.0'] # noqa: E221 cuda_all_gpu_architectures += ['7.0', '7.2'] # noqa: E221 # https://docs.nvidia.com/cuda/archive/9.0/cuda-toolkit-release-notes/index.html#unsupported-features cuda_lo_limit_gpu_architecture = '3.0' # noqa: E221 if version_compare(cuda_version, '<10.0'): cuda_common_gpu_architectures += ['7.2+PTX'] # noqa: E221 cuda_hi_limit_gpu_architecture = '8.0' # noqa: E221 if version_compare(cuda_version, '>=10.0'): cuda_known_gpu_architectures += ['Turing'] # noqa: E221 cuda_common_gpu_architectures += ['7.5'] # noqa: E221 cuda_all_gpu_architectures += ['7.5'] # noqa: E221 if version_compare(cuda_version, '<11.0'): cuda_common_gpu_architectures += ['7.5+PTX'] # noqa: E221 cuda_hi_limit_gpu_architecture = '8.0' # noqa: E221 if version_compare(cuda_version, '>=11.0'): cuda_known_gpu_architectures += ['Ampere'] # noqa: E221 cuda_common_gpu_architectures += ['8.0'] # noqa: E221 cuda_all_gpu_architectures += ['8.0'] # noqa: E221 # https://docs.nvidia.com/cuda/archive/11.0/cuda-toolkit-release-notes/index.html#deprecated-features cuda_lo_limit_gpu_architecture = '3.5' # noqa: E221 if version_compare(cuda_version, '<11.1'): cuda_common_gpu_architectures += ['8.0+PTX'] # noqa: E221 cuda_hi_limit_gpu_architecture = '8.6' # noqa: E221 if version_compare(cuda_version, '>=11.1'): cuda_common_gpu_architectures += ['8.6', '8.6+PTX'] # noqa: E221 cuda_all_gpu_architectures += ['8.6'] # noqa: E221 if version_compare(cuda_version, '<12.0'): cuda_hi_limit_gpu_architecture = '9.0' # noqa: E221 if not cuda_arch_list: cuda_arch_list = 'Auto' if cuda_arch_list == 'All': # noqa: E271 cuda_arch_list = cuda_known_gpu_architectures elif cuda_arch_list == 'Common': # noqa: E271 cuda_arch_list = cuda_common_gpu_architectures elif cuda_arch_list == 'Auto': # noqa: E271 if detected: if isinstance(detected, list): cuda_arch_list = detected else: cuda_arch_list = self._break_arch_string(detected) cuda_arch_list = self._filter_cuda_arch_list(cuda_arch_list, cuda_lo_limit_gpu_architecture, cuda_hi_limit_gpu_architecture, cuda_common_gpu_architectures[-1]) else: cuda_arch_list = cuda_common_gpu_architectures elif isinstance(cuda_arch_list, str): cuda_arch_list = self._break_arch_string(cuda_arch_list) cuda_arch_list = sorted(x for x in set(cuda_arch_list) if x) cuda_arch_bin = [] cuda_arch_ptx = [] for arch_name in cuda_arch_list: arch_bin = [] arch_ptx = [] add_ptx = arch_name.endswith('+PTX') if add_ptx: arch_name = arch_name[:-len('+PTX')] if re.fullmatch('[0-9]+\\.[0-9](\\([0-9]+\\.[0-9]\\))?', arch_name): arch_bin, arch_ptx = [arch_name], [arch_name] else: arch_bin, arch_ptx = { 'Fermi': (['2.0', '2.1(2.0)'], []), 'Kepler+Tegra': (['3.2'], []), 'Kepler+Tesla': (['3.7'], []), 'Kepler': (['3.0', '3.5'], ['3.5']), 'Maxwell+Tegra': (['5.3'], []), 'Maxwell': (['5.0', '5.2'], ['5.2']), 'Pascal': (['6.0', '6.1'], ['6.1']), 'Pascal+Tegra': (['6.2'], []), 'Volta': (['7.0'], ['7.0']), 'Xavier': (['7.2'], []), 'Turing': (['7.5'], ['7.5']), 'Ampere': (['8.0'], ['8.0']), }.get(arch_name, (None, None)) if arch_bin is None: raise InvalidArguments(f'Unknown CUDA Architecture Name {arch_name}!') cuda_arch_bin += arch_bin if add_ptx: if not arch_ptx: arch_ptx = arch_bin cuda_arch_ptx += arch_ptx cuda_arch_bin = sorted(list(set(cuda_arch_bin))) cuda_arch_ptx = sorted(list(set(cuda_arch_ptx))) nvcc_flags = [] nvcc_archs_readable = [] for arch in cuda_arch_bin: arch, codev = re.fullmatch( '([0-9]+\\.[0-9])(?:\\(([0-9]+\\.[0-9])\\))?', arch).groups() if version_compare(arch, '<' + cuda_lo_limit_gpu_architecture): continue if version_compare(arch, '>=' + cuda_hi_limit_gpu_architecture): continue if codev: arch = arch.replace('.', '') codev = codev.replace('.', '') nvcc_flags += ['-gencode', 'arch=compute_' + codev + ',code=sm_' + arch] nvcc_archs_readable += ['sm_' + arch] else: arch = arch.replace('.', '') nvcc_flags += ['-gencode', 'arch=compute_' + arch + ',code=sm_' + arch] nvcc_archs_readable += ['sm_' + arch] for arch in cuda_arch_ptx: arch, codev = re.fullmatch( '([0-9]+\\.[0-9])(?:\\(([0-9]+\\.[0-9])\\))?', arch).groups() if codev: arch = codev if version_compare(arch, '<' + cuda_lo_limit_gpu_architecture): continue if version_compare(arch, '>=' + cuda_hi_limit_gpu_architecture): continue arch = arch.replace('.', '') nvcc_flags += ['-gencode', 'arch=compute_' + arch + ',code=compute_' + arch] nvcc_archs_readable += ['compute_' + arch] return nvcc_flags, nvcc_archs_readable def initialize(*args, **kwargs): return CudaModule(*args, **kwargs)