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spack/var/spack/repos/builtin/packages/lbann/package.py
Brian Van Essen 7dea225fce
Update lbann version and simplify installation (#19579) 
* Added hash values for LBANN v0.101 and Hydrogen v1.5.0.  Updated the
LBANN package to be more successful in resolving a legal configuration
of MPI and HWLOC packages.  This required the removal of the MPI
virtual package since it is unable to resolve dependencies with
minimum version requirements. As a result to enable a reasonable
install line for LBANN this requires explicit forwarding of MPI
variants to Hydrogen and Aluminum.  Due to the lack of variant
forwarding, there are many explicitly replicated dependencies for both
LBANN and Hydrogen.  Fixed the error in LBANN where gpu variant was
replaced by the cuda variant, but not all dependencies were fixed.

* Fixed the minumum cuDNN version for newer versions of LBANN.

* Added explicit versioning of the MPI libraries for DiHydrogen to avoid
all of the conflicts with minimum required versions of the OpenMPI library.

* Removed explicit MPI versions and went back to using the MPI virtual
dependency.  Updated construction of variant forwarding to use
iterative construction of constraints and variants.  This exacerbates
the challenges with backtracking in the current concretizer, but
should be fixed in the new concretizer.

* Added support for including the DiHydrogen library in LBANN as well as
support for the distributed convolution (DistConv) parallel
algorithms.  Also include support for building with half precision.

* Moving dependencies around

* Added conflict statement to ensure that the variant dihydrogen is
required for distconv.

* Removed the preferred field

* Fixed Flake8 and cuDNN version bounds
2020-10-30 14:51:10 -05:00

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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)
import os
import sys
from spack import *
class Lbann(CMakePackage, CudaPackage):
"""LBANN: Livermore Big Artificial Neural Network Toolkit. A distributed
memory, HPC-optimized, model and data parallel training toolkit for deep
neural networks."""
homepage = "http://software.llnl.gov/lbann/"
url = "https://github.com/LLNL/lbann/archive/v0.91.tar.gz"
git = "https://github.com/LLNL/lbann.git"
maintainers = ['bvanessen']
version('develop', branch='develop')
version('0.101', sha256='69d3fe000a88a448dc4f7e263bcb342c34a177bd9744153654528cd86335a1f7')
version('0.100', sha256='d1bab4fb6f1b80ae83a7286cc536a32830890f6e5b0c3107a17c2600d0796912')
version('0.99', sha256='3358d44f1bc894321ce07d733afdf6cb7de39c33e3852d73c9f31f530175b7cd')
version('0.98.1', sha256='9a2da8f41cd8bf17d1845edf9de6d60f781204ebd37bffba96d8872036c10c66')
version('0.98', sha256='8d64b9ac0f1d60db553efa4e657f5ea87e790afe65336117267e9c7ae6f68239')
version('0.97.1', sha256='2f2756126ac8bb993202cf532d72c4d4044e877f4d52de9fdf70d0babd500ce4')
version('0.97', sha256='9794a706fc7ac151926231efdf74564c39fbaa99edca4acb745ee7d20c32dae7')
version('0.96', sha256='97af78e9d3c405e963361d0db96ee5425ee0766fa52b43c75b8a5670d48e4b4a')
version('0.95', sha256='d310b986948b5ee2bedec36383a7fe79403721c8dc2663a280676b4e431f83c2')
version('0.94', sha256='567e99b488ebe6294933c98a212281bffd5220fc13a0a5cd8441f9a3761ceccf')
version('0.93', sha256='77bfd7fe52ee7495050f49bcdd0e353ba1730e3ad15042c678faa5eeed55fb8c')
version('0.92', sha256='9187c5bcbc562c2828fe619d53884ab80afb1bcd627a817edb935b80affe7b84')
version('0.91', sha256='b69f470829f434f266119a33695592f74802cff4b76b37022db00ab32de322f5')
variant('opencv', default=True, description='Builds with support for image processing routines with OpenCV')
variant('seq_init', default=False, description='Force serial initialization of weight matrices.')
variant('dtype', default='float',
description='Type for floating point representation of weights',
values=('float', 'double'))
variant('build_type', default='Release',
description='The build type to build',
values=('Debug', 'Release'))
variant('al', default=True, description='Builds with support for Aluminum Library')
variant('conduit', default=True,
description='Builds with support for Conduit Library '
'(note that for v0.99 conduit is required)')
variant('half', default=False,
description='Builds with support for FP16 precision data types')
variant('dihydrogen', default=False,
description='Builds with support for DiHydrogen Tensor Library')
variant('distconv', default=False,
description='Builds with support for spatial, filter, or channel '
'distributed convolutions')
variant('vtune', default=False, description='Builds with support for Intel VTune')
variant('docs', default=False, description='Builds with support for building documentation')
variant('extras', default=False, description='Add python modules for LBANN related tools')
conflicts('@:0.90,0.99:', when='~conduit')
depends_on('cmake@3.16.0:', type='build')
# Specify the correct versions of Hydrogen
depends_on('hydrogen@:1.3.4', when='@0.95:0.100')
depends_on('hydrogen@1.4.0:1.4.99', when='@0.101:0.101.99')
depends_on('hydrogen@1.5.0:', when='@:0.90,0.102:')
# Add Hydrogen variants
depends_on('hydrogen +openmp_blas +shared +int64')
depends_on('hydrogen +al', when='+al')
depends_on('hydrogen +cuda', when='+cuda')
depends_on('hydrogen +half', when='+half')
depends_on('hydrogen build_type=Debug', when='build_type=Debug')
# Older versions depended on Elemental not Hydrogen
depends_on('elemental +openmp_blas +shared +int64', when='@0.91:0.94')
depends_on('elemental +openmp_blas +shared +int64 build_type=Debug',
when='build_type=Debug @0.91:0.94')
# Specify the correct version of Aluminum
depends_on('aluminum@:0.3.99', when='@0.95:0.100 +al')
depends_on('aluminum@0.4:0.4.99', when='@0.101:0.101.99 +al')
depends_on('aluminum@0.5:', when='@:0.90,0.102: +al')
# Add Aluminum variants
depends_on('aluminum +cuda +nccl +ht +cuda_rma', when='+al +cuda')
depends_on('dihydrogen +openmp', when='+dihydrogen')
depends_on('dihydrogen +cuda', when='+dihydrogen +cuda')
depends_on('dihydrogen +al', when='+dihydrogen +al')
depends_on('dihydrogen +legacy +cuda', when='+distconv')
depends_on('dihydrogen +half', when='+dihydrogen +half')
depends_on('dihydrogen@0.1', when='@0.101:0.101.99 +dihydrogen')
depends_on('dihydrogen@:0.0,0.2:', when='@:0.90,0.102: +dihydrogen')
conflicts('~dihydrogen', when='+distconv')
depends_on('cudnn', when='@0.90:0.100.99 +cuda')
depends_on('cudnn@8.0.2:', when='@:0.90,0.101: +cuda')
depends_on('cub', when='@0.94:0.98.2 +cuda')
depends_on('mpi')
depends_on('hwloc@2.0:')
depends_on('half', when='+half')
# LBANN wraps OpenCV calls in OpenMP parallel loops, build without OpenMP
# Additionally disable video related options, they incorrectly link in a
# bad OpenMP library when building with clang or Intel compilers
depends_on('opencv@4.1.0: build_type=RelWithDebInfo +core +highgui +imgproc +jpeg '
'+png +tiff +zlib +fast-math ~calib3d ~cuda ~dnn ~eigen'
'~features2d ~flann ~gtk ~ipp ~ipp_iw ~jasper ~java ~lapack ~ml'
'~openmp ~opencl ~opencl_svm ~openclamdblas ~openclamdfft'
'~pthreads_pf ~python ~qt +shared ~stitching ~superres ~ts'
'~video ~videostab ~videoio ~vtk', when='+opencv')
# Note that for Power systems we want the environment to add +powerpc +vsx
depends_on('opencv@4.1.0: +powerpc +vsx', when='+opencv arch=ppc64le:')
depends_on('cnpy')
depends_on('nccl', when='@0.94:0.98.2 +cuda')
depends_on('conduit@0.4.0: +hdf5~hdf5_compat', when='@0.94:0.99 +conduit')
depends_on('conduit@0.4.0: +hdf5~hdf5_compat', when='@:0.90,0.99:')
depends_on('python@3:3.7.9 +shared', type=('build', 'run'), when='@:0.90,0.99:')
extends("python")
depends_on('py-setuptools', type='build')
depends_on('py-argparse', type='run', when='@:0.90,0.99: ^python@:2.6')
depends_on('py-configparser', type='run', when='@:0.90,0.99: +extras')
depends_on('py-graphviz@0.10.1:', type='run', when='@:0.90,0.99: +extras')
depends_on('py-matplotlib@3.0.0:', type='run', when='@:0.90,0.99: +extras')
depends_on('py-numpy@1.16.0:', type=('build', 'run'), when='@:0.90,0.99: +extras')
depends_on('py-onnx@1.3.0:', type='run', when='@:0.90,0.99: +extras')
depends_on('py-pandas@0.24.1:', type='run', when='@:0.90,0.99: +extras')
depends_on('py-texttable@1.4.0:', type='run', when='@:0.90,0.99: +extras')
depends_on('py-pytest', type='test', when='@:0.90,0.99:')
depends_on('py-protobuf+cpp@3.10.0', type=('build', 'run'), when='@:0.90,0.99:')
depends_on('protobuf+shared@3.10.0', when='@:0.90,0.99:')
depends_on('py-breathe', type='build', when='+docs')
depends_on('doxygen', type='build', when='+docs')
depends_on('py-m2r', type='build', when='+docs')
depends_on('cereal')
depends_on('catch2', type='test')
depends_on('clara')
generator = 'Ninja'
depends_on('ninja', type='build')
@property
def common_config_args(self):
spec = self.spec
# Environment variables
cppflags = []
cppflags.append('-DLBANN_SET_EL_RNG -ldl')
return [
'-DCMAKE_CXX_FLAGS=%s' % ' '.join(cppflags),
'-DLBANN_VERSION=spack',
'-DCNPY_DIR={0}'.format(spec['cnpy'].prefix),
]
# Get any recent versions or non-numeric version
# Note that develop > numeric and non-develop < numeric
@when('@:0.90,0.94:')
def cmake_args(self):
spec = self.spec
args = self.common_config_args
args.extend([
'-DLBANN_WITH_TOPO_AWARE:BOOL=%s' % ('+cuda +nccl' in spec),
'-DLBANN_WITH_ALUMINUM:BOOL=%s' % ('+al' in spec),
'-DLBANN_WITH_CONDUIT:BOOL=%s' % ('+conduit' in spec),
'-DLBANN_WITH_CUDA:BOOL=%s' % ('+cuda' in spec),
'-DLBANN_WITH_CUDNN:BOOL=%s' % ('+cuda' in spec),
'-DLBANN_WITH_SOFTMAX_CUDA:BOOL=%s' % ('+cuda' in spec),
'-DLBANN_SEQUENTIAL_INITIALIZATION:BOOL=%s' %
('+seq_init' in spec),
'-DLBANN_WITH_TBINF=OFF',
'-DLBANN_WITH_VTUNE:BOOL=%s' % ('+vtune' in spec),
'-DLBANN_DATATYPE={0}'.format(spec.variants['dtype'].value),
'-DLBANN_VERBOSE=0',
'-DCEREAL_DIR={0}'.format(spec['cereal'].prefix),
# protobuf is included by py-protobuf+cpp
'-DProtobuf_DIR={0}'.format(spec['protobuf'].prefix)])
if spec.satisfies('@:0.90') or spec.satisfies('@0.95:'):
args.extend([
'-DHydrogen_DIR={0}/CMake/hydrogen'.format(
spec['hydrogen'].prefix)])
elif spec.satisfies('@0.94'):
args.extend([
'-DElemental_DIR={0}/CMake/elemental'.format(
spec['elemental'].prefix)])
if spec.satisfies('@0.94:0.98.2'):
args.extend(['-DLBANN_WITH_NCCL:BOOL=%s' %
('+cuda +nccl' in spec)])
if '+vtune' in spec:
args.extend(['-DVTUNE_DIR={0}'.format(spec['vtune'].prefix)])
if '+al' in spec:
args.extend(['-DAluminum_DIR={0}'.format(spec['aluminum'].prefix)])
if '+conduit' in spec:
args.extend([
'-DLBANN_CONDUIT_DIR={0}'.format(spec['conduit'].prefix),
'-DConduit_DIR={0}'.format(spec['conduit'].prefix)])
# Add support for OpenMP
if spec.satisfies('%clang') or spec.satisfies('%apple-clang'):
if sys.platform == 'darwin':
clang = self.compiler.cc
clang_bin = os.path.dirname(clang)
clang_root = os.path.dirname(clang_bin)
args.extend([
'-DOpenMP_CXX_FLAGS=-fopenmp=libomp',
'-DOpenMP_CXX_LIB_NAMES=libomp',
'-DOpenMP_libomp_LIBRARY={0}/lib/libomp.dylib'.format(
clang_root)])
if '+opencv' in spec:
args.extend(['-DOpenCV_DIR:STRING={0}'.format(
spec['opencv'].prefix)])
if '+cuda' in spec:
args.extend([
'-DCUDA_TOOLKIT_ROOT_DIR={0}'.format(
spec['cuda'].prefix)])
args.extend([
'-DcuDNN_DIR={0}'.format(
spec['cudnn'].prefix)])
if spec.satisfies('@0.94:0.98.2'):
args.extend(['-DCUB_DIR={0}'.format(
spec['cub'].prefix)])
if '+nccl' in spec:
args.extend([
'-DNCCL_DIR={0}'.format(
spec['nccl'].prefix)])
if spec.satisfies('@:0.90') or spec.satisfies('@0.100:'):
args.extend([
'-DLBANN_WITH_DIHYDROGEN:BOOL=%s' % ('+dihydrogen' in spec)])
if spec.satisfies('@:0.90') or spec.satisfies('@0.101:'):
args.extend([
'-DLBANN_WITH_DISTCONV:BOOL=%s' % ('+distconv' in spec)])
return args
@when('@0.91:0.93')
def cmake_args(self):
spec = self.spec
args = self.common_config_args
args.extend([
'-DWITH_CUDA:BOOL=%s' % ('+cuda' in spec),
'-DWITH_CUDNN:BOOL=%s' % ('+cuda' in spec),
'-DELEMENTAL_USE_CUBLAS:BOOL=%s' % (
'+cublas' in spec['elemental']),
'-DWITH_TBINF=OFF',
'-DWITH_VTUNE=OFF',
'-DElemental_DIR={0}'.format(spec['elemental'].prefix),
'-DELEMENTAL_MATH_LIBS={0}'.format(
spec['elemental'].libs),
'-DSEQ_INIT:BOOL=%s' % ('+seq_init' in spec),
'-DVERBOSE=0',
'-DLBANN_HOME=.'])
if spec.variants['dtype'].value == 'float':
args.extend(['-DDATATYPE=4'])
elif spec.variants['dtype'].value == 'double':
args.extend(['-DDATATYPE=8'])
if '+opencv' in spec:
args.extend(['-DOpenCV_DIR:STRING={0}'.format(
spec['opencv'].prefix)])
if '+cudnn' in spec:
args.extend(['-DcuDNN_DIR={0}'.format(
spec['cudnn'].prefix)])
if '+cub' in spec:
args.extend(['-DCUB_DIR={0}'.format(
spec['cub'].prefix)])
return args
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