Added a package for the DiHydrogen distributed linear algebra library. (#15426)

* Added a package for the DiHydrogen distributed linear algebra library.

* Updated recipe to provide cuda architecture constaints.

* Addressed reviewer comments

* Fixed flake 8
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Brian Van Essen 2020-03-18 09:46:49 -07:00 committed by GitHub
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# Copyright 2013-2020 Lawrence Livermore National Security, LLC and other
# Spack Project Developers. See the top-level COPYRIGHT file for details.
#
# SPDX-License-Identifier: (Apache-2.0 OR MIT)
from spack import *
class Dihydrogen(CMakePackage, CudaPackage):
"""DiHydrogen is the second version of the Hydrogen fork of the
well-known distributed linear algebra library,
Elemental. DiHydrogen aims to be a basic distributed
multilinear algebra interface with a particular emphasis on the
needs of the distributed machine learning effort, LBANN."""
homepage = "https://github.com/LLNL/DiHydrogen.git"
git = "https://github.com/LLNL/DiHydrogen.git"
maintainers = ['bvanessen']
version('master', branch='master')
variant('al', default=True,
description='Builds with Aluminum communication library')
variant('developer', default=False,
description='Enable extra warnings and force tests to be enabled.')
variant('half', default=False,
description='Enable FP16 support on the CPU.')
variant('legacy', default=False,
description='Enable the legacy DistConv code branch.')
variant('nvshmem', default=False,
description='Builds with support for NVSHMEM')
variant('openmp', default=False,
description='Enable CPU acceleration with OpenMP threads.')
variant('rocm', default=False,
description='Enable ROCm/HIP language features.')
variant('shared', default=True,
description='Enables the build of shared libraries')
# Override the default set of CUDA architectures with the relevant
# subset from lib/spack/spack/build_systems/cuda.py
cuda_arch_values = [
'60', '61', '62',
'70', '72', '75',
]
variant('cuda_arch',
description='CUDA architecture',
values=spack.variant.auto_or_any_combination_of(*cuda_arch_values))
depends_on('mpi')
depends_on('catch2', type='test')
depends_on('aluminum', when='+al ~cuda')
depends_on('aluminum +gpu +nccl +mpi_cuda', when='+al +cuda')
depends_on('cuda', when=('+cuda' or '+legacy'))
depends_on('cudnn', when=('+cuda' or '+legacy'))
depends_on('cub', when=('+cuda' or '+legacy'))
# Legacy builds require cuda
conflicts('~cuda', when='+legacy')
depends_on('half', when='+half')
generator = 'Ninja'
depends_on('ninja', type='build')
depends_on('cmake@3.14.0:', type='build')
illegal_cuda_arch_values = [
'10', '11', '12', '13',
'20', '21',
'30', '32', '35', '37',
'50', '52', '53',
]
for value in illegal_cuda_arch_values:
conflicts('cuda_arch=' + value)
@property
def libs(self):
shared = True if '+shared' in self.spec else False
return find_libraries(
'libH2Core', root=self.prefix, shared=shared, recursive=True
)
def cmake_args(self):
spec = self.spec
args = [
'-DCMAKE_INSTALL_MESSAGE:STRING=LAZY',
'-DBUILD_SHARED_LIBS:BOOL=%s' % ('+shared' in spec),
'-DH2_ENABLE_CUDA=%s' % ('+cuda' in spec),
'-DH2_ENABLE_DISTCONV_LEGACY=%s' % ('+legacy' in spec),
'-DH2_ENABLE_OPENMP=%s' % ('+openmp' in spec),
'-DH2_ENABLE_FP16=%s' % ('+half' in spec),
'-DH2_ENABLE_HIP_ROCM=%s' % ('+rocm' in spec),
'-DH2_DEVELOPER_BUILD=%s' % ('+developer' in spec),
]
if '+cuda' in spec:
cuda_arch = spec.variants['cuda_arch'].value
if len(cuda_arch) == 1 and cuda_arch[0] == 'auto':
args.append('-DCMAKE_CUDA_FLAGS=-arch=sm_60')
else:
cuda_arch = [x for x in spec.variants['cuda_arch'].value
if x != 'auto']
if cuda_arch:
args.append('-DCMAKE_CUDA_FLAGS={0}'.format(
' '.join(self.cuda_flags(cuda_arch))
))
return args