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new file: b/Boost/Boost-1.68.0-intel-2018.04.eb
new file: l/libMesh/libMesh-1.3.0-intel-2018.04.eb new file: l/libMesh/libMesh-1.4.1-intel-2018.04.eb new file: m/MUMPS/MUMPS-5.2.0-intel-2018.04-parmetis.eb new file: p/PETSc/PETSc-3.7.5-intel-2018.04-it4i.eb new file: s/SCOTCH/SCOTCH-6.0.6-intel-2018.04.eb
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b/Boost/Boost-1.68.0-intel-2018.04.eb
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b/Boost/Boost-1.68.0-intel-2018.04.eb
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# IT4Innovations 2018
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name = 'Boost'
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version = '1.68.0'
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homepage = 'http://www.boost.org/'
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description = """Boost provides free peer-reviewed portable C++ source libraries."""
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toolchain = {'name': 'intel', 'version': '2018.04'}
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toolchainopts = {'pic': True, 'usempi': True}
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source_urls = [SOURCEFORGE_SOURCE]
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sources = ['%%(namelower)s_%s.tar.gz' % '_'.join(version.split('.'))]
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dependencies = [
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('bzip2', '1.0.6', '', True),
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('zlib', '1.2.11', '', True),
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]
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configopts = '--without-libraries=python'
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# also build boost_mpi
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boost_mpi = True
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moduleclass = 'devel'
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36
l/libMesh/libMesh-1.3.0-intel-2018.04.eb
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l/libMesh/libMesh-1.3.0-intel-2018.04.eb
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# IT4Innovations 2019
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easyblock = 'ConfigureMake'
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name = 'libMesh'
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version = '1.3.0'
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homepage = 'http://libmesh.github.io/'
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description = """The libMesh library provides a framework for the numerical simulation of partial differential equations
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using arbitrary unstructured discretizations on serial and parallel platforms. A major goal of the library is to
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provide support for adaptive mesh refinement (AMR) computations in parallel while allowing a research scientist
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to focus on the physics they are modeling."""
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toolchain = {'name': 'intel', 'version': '2018.04'}
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toolchainopts = {'pic': True, 'usempi': True}
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source_urls = [
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'https://github.com/libMesh/libmesh/releases/download/v%(version)s/',
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]
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sources = [SOURCELOWER_TAR_GZ]
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configopts = " --with-metis=PETSc"
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dependencies = [
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#('ParMETIS', '4.0.3'),
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('Boost', '1.68.0'),
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('PETSc' ,'3.7.5', '-it4i'),
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]
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sanity_check_paths = {
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'files': ['bin/meshtool-opt'],
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'dirs': ['bin'],
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}
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moduleclass = 'lib'
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l/libMesh/libMesh-1.4.1-intel-2018.04.eb
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l/libMesh/libMesh-1.4.1-intel-2018.04.eb
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# IT4Innovations 2019
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easyblock = 'ConfigureMake'
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name = 'libMesh'
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version = '1.4.1'
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homepage = 'http://libmesh.github.io/'
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description = """The libMesh library provides a framework for the numerical simulation of partial differential equations
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using arbitrary unstructured discretizations on serial and parallel platforms. A major goal of the library is to
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provide support for adaptive mesh refinement (AMR) computations in parallel while allowing a research scientist
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to focus on the physics they are modeling."""
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toolchain = {'name': 'intel', 'version': '2018.04'}
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toolchainopts = {'pic': True, 'usempi': True}
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source_urls = [
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'https://github.com/libMesh/libmesh/releases/download/v%(version)s/',
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]
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sources = [SOURCELOWER_TAR_GZ]
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configopts = " --with-metis=PETSc"
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dependencies = [
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#('ParMETIS', '4.0.3'),
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('Boost', '1.68.0'),
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('PETSc' ,'3.7.5', '-it4i'),
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]
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sanity_check_paths = {
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'files': ['bin/meshtool-opt'],
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'dirs': ['bin'],
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}
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moduleclass = 'lib'
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m/MUMPS/MUMPS-5.2.0-intel-2018.04-parmetis.eb
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m/MUMPS/MUMPS-5.2.0-intel-2018.04-parmetis.eb
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# IT4Innovations 2019
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name = 'MUMPS'
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version = '5.2.0'
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versionsuffix = '-parmetis'
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homepage = 'http://graal.ens-lyon.fr/MUMPS/'
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description = "A parallel sparse direct solver"
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toolchain = {'name': 'intel', 'version': '2018.04'}
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toolchainopts = {'pic': True, 'usempi': True}
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source_urls = ['http://mumps.enseeiht.fr/']
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sources = ['%(name)s_%(version)s.tar.gz']
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dependencies = [
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('SCOTCH', '6.0.6'),
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('ParMETIS', '4.0.3'),
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]
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parallel = 1
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buildopts = 'all'
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moduleclass = 'math'
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p/PETSc/PETSc-3.7.5-intel-2018.04-it4i.eb
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p/PETSc/PETSc-3.7.5-intel-2018.04-it4i.eb
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# IT4Innovations 2019
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easyblock = 'ConfigureMake'
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name = 'PETSc'
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version = '3.7.5'
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versionsuffix = '-it4i'
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homepage = 'http://www.mcs.anl.gov/petsc'
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description = """PETSc, pronounced PET-see (the S is silent), is a suite of data structures and routines for the
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scalable (parallel) solution of scientific applications modeled by partial differential equations."""
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toolchain = {'name': 'intel', 'version': '2018.04'}
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# build is still parallel, PETSc make doesnt support -j opt
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maxparallel = 0
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source_urls = ['http://ftp.mcs.anl.gov/pub/petsc/release-snapshots']
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sources = [SOURCELOWER_TAR_GZ]
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# (build) dependencies provided through EasyBuild
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builddependencies = [('CMake', '3.14.1', '', True)]
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# configure installs dependencies -> remove installdir before configure
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keeppreviousinstall = True
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preconfigopts = 'rm -rf %(installdir)s;'
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petscArch = 'intel-opt'
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petscDir = '%(builddir)s/%(namelower)s-%(version)s'
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# config options
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configopts = '--CFLAGS=-O3 -xHost --CXXFLAGS=-O3 -xHost --FFLAGS=-O3 -xHost --with-c++-support --with-pic=1 '
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configopts += '--with-cc=mpicc --with-cxx=mpicxx --with-fc=mpif90 --with-debugging=0 --with-gnu-compilers=0 '
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configopts += '--with-mpi=1 --with-x=0 '
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configopts += '--download-metis --download-parmetis --download-mumps --download-superlu --download-superlu_dist '
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configopts += '--with-blas-lapack-lib=[$EBROOTIMKL/mkl/lib/intel64_lin/libmkl_intel_lp64.a,libmkl_sequential.a,libmkl_core.a] '
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configopts += '--with-scalapack-include=$EBROOTIMKL/mkl/include '
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configopts += '--with-scalapack-lib=[$EBROOTIMKL/mkl/lib/intel64_lin/libmkl_scalapack_lp64.a,libmkl_blacs_intelmpi_lp64.a,libmkl_intel_lp64.a,libmkl_sequential.a,libmkl_core.a] '
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configopts += '--with-scalapack=1 '
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configopts += 'PETSC_ARCH=%s' % petscArch
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installopts = 'PETSC_DIR=%s PETSC_ARCH=%s' % (petscDir, petscArch)
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buildopts = installopts + ' all'
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modextravars = {'PETSC_DIR': '%(installdir)s'}
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moduleclass = 'numlib'
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# sanity checks
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runtest = 'test' # run make test after make
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sanity_check_paths = {
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'files': ['include/petscconf.h', 'lib/libpetsc.so'],
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'dirs': []
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}
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sanity_check_commands = [('petscmpiexec', '-h')]
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s/SCOTCH/SCOTCH-6.0.6-intel-2018.04.eb
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s/SCOTCH/SCOTCH-6.0.6-intel-2018.04.eb
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# IT4Innovations 2019
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name = 'SCOTCH'
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version = '6.0.6'
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homepage = 'http://gforge.inria.fr/projects/scotch/'
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description = """Software package and libraries for sequential and parallel graph partitioning,
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static mapping, and sparse matrix block ordering, and sequential mesh and hypergraph partitioning."""
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toolchain = {'name': 'intel', 'version': '2018.04'}
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toolchainopts = {'pic': True}
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source_urls = ['http://gforge.inria.fr/frs/download.php/file/34618/']
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sources = ['%(namelower)s_%(version)s.tar.gz']
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moduleclass = 'math'
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