56952aaf1f
* Creating a spack package for LLNL's LBANN (Livermore Big Artificial Neural Network) training toolkit. * Recipe for building LBANN toolkit. Contains limited feature set and is optimized for building with GNU gcc and OpenBLAS. * Removed unnecessary dependencies based on reviewers feedback. * Added support for the int64 data type in the Elemental library. This is required for supporting indices for large matrices. * Added a variant to force a sequential weight matrix initialization. This is slow, but provides an initialization that is independent of model parallelism. * Added a guard to prevent building Elemental with the Intel compiler for versions that have known bugs.
84 lines
3.4 KiB
Python
84 lines
3.4 KiB
Python
##############################################################################
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# Copyright (c) 2013-2016, Lawrence Livermore National Security, LLC.
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# Produced at the Lawrence Livermore National Laboratory.
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#
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# This file is part of Spack.
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# Created by Todd Gamblin, tgamblin@llnl.gov, All rights reserved.
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# LLNL-CODE-647188
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#
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# For details, see https://github.com/llnl/spack
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# Please also see the LICENSE file for our notice and the LGPL.
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#
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# This program is free software; you can redistribute it and/or modify
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# it under the terms of the GNU Lesser General Public License (as
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# published by the Free Software Foundation) version 2.1, February 1999.
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#
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# This program is distributed in the hope that it will be useful, but
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# WITHOUT ANY WARRANTY; without even the IMPLIED WARRANTY OF
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# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the terms and
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# conditions of the GNU Lesser General Public License for more details.
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#
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# You should have received a copy of the GNU Lesser General Public
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# License along with this program; if not, write to the Free Software
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# Foundation, Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA
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##############################################################################
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from spack import *
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class Lbann(CMakePackage):
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"""LBANN: Livermore Big Artificial Neural Network Toolkit. A distributed
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memory, HPC-optimized, model and data parallel training toolkit for deep
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neural networks."""
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homepage = "http://software.llnl.gov/lbann/"
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url = "https://github.com/LLNL/lbann/archive/v0.91.tar.gz"
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version('develop', git='https://github.com/LLNL/lbann.git', branch="develop")
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version('0.91', '83b0ec9cd0b7625d41dfb06d2abd4134')
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variant('debug', default=False, description='Builds a debug version of the libraries')
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variant('gpu', default=False, description='Builds with support for GPUs via CUDA and cuDNN')
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variant('opencv', default=True, description='Builds with support for image processing routines with OpenCV')
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variant('seq_init', default=False, description='Force serial initialization of weight matrices.')
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depends_on('elemental +openmp_blas +scalapack +shared +int64')
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depends_on('elemental +openmp_blas +scalapack +shared +int64 +debug', when='+debug')
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depends_on('cuda', when='+gpu')
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depends_on('mpi')
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depends_on('opencv@2.4.13', when='+opencv')
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depends_on('protobuf@3.0.2')
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def build_type(self):
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if '+debug' in self.spec:
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return 'Debug'
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else:
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return 'Release'
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def cmake_args(self):
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spec = self.spec
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# Environment variables
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CPPFLAGS = []
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CPPFLAGS.append('-DLBANN_SET_EL_RNG')
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if '~seq_init' in spec:
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CPPFLAGS.append('-DLBANN_PARALLEL_RANDOM_MATRICES')
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args = [
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'-DCMAKE_INSTALL_MESSAGE=LAZY',
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'-DCMAKE_CXX_FLAGS=%s' % ' '.join(CPPFLAGS),
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'-DWITH_CUDA:BOOL=%s' % ('+gpu' in spec),
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'-DWITH_CUDNN:BOOL=%s' % ('+gpu' in spec),
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'-DWITH_TBINF=OFF',
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'-DWITH_VTUNE=OFF',
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'-DElemental_DIR={0}'.format(self.spec['elemental'].prefix),
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'-DELEMENTAL_MATH_LIBS={0}'.format(
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self.spec['elemental'].elemental_libs),
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'-DVERBOSE=0',
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'-DLBANN_HOME=.',
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'-DLBANN_VER=spack']
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if '+opencv' in self.spec:
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args.extend(['-DOpenCV_DIR:STRING={0}'.format(
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self.spec['opencv'].prefix)])
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return args
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