new file: a/Automake/Automake-1.17-GCCcore-14.2.0.eb

deleted:    c/CASTEP/CASTEP-25.12-foss-2023b.eb
	new file:   c/CASTEP/CASTEP-25.12-intel-2024a.eb
	new file:   n/NCCL/NCCL-2.21.5-GCCcore-14.2.0-CUDA-12.8.0.eb
	modified:   n/NVHPC/NVHPC-24.9-CUDA-12.6.0.eb
	new file:   n/NVHPC/NVHPC-25.3-CUDA-12.8.0.eb
	new file:   o/OpenMPI/OpenMPI-5.0.7-25.3-CUDA-12.8.0.eb
	new file:   o/OpenMPI/OpenMPI-5.0.7-GCC-14.2.0.eb
	new file:   u/UCC-CUDA/UCC-CUDA-1.3.0-GCCcore-14.2.0-CUDA-12.8.0.eb
	deleted:    u/UCC/UCC-1.3.0-GCCcore-14.2.0.eb
	new file:   v/VASP/VASP-6.5.1-NVHPC-24.3-CUDA-12.3.0-adjust-makefile.patch
	new file:   v/VASP/VASP-6.5.1-NVHPC-24.3-CUDA-12.3.0.eb
	new file:   v/VASP/VASP-6.5.1-intel-2024a.eb
	new file:   v/VASP/VASP-6.5.1-intel-hdf5.patch
This commit is contained in:
Lukas Krupcik 2025-04-11 09:10:46 +02:00
parent bb451554fc
commit 64aa7c8083
14 changed files with 652 additions and 130 deletions

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@ -0,0 +1,46 @@
# IT4Innovations
# LK 2025
easyblock = 'ConfigureMake'
name = 'Automake'
version = '1.17'
homepage = 'https://www.gnu.org/software/automake/automake.html'
description = "Automake: GNU Standards-compliant Makefile generator"
toolchain = {'name': 'GCCcore', 'version': '14.2.0'}
source_urls = [GNU_SOURCE]
sources = [SOURCELOWER_TAR_GZ]
patches = ['Automake-%(version)s_perl_env_space.patch']
checksums = [
{'automake-1.17.tar.gz': '397767d4db3018dd4440825b60c64258b636eaf6bf99ac8b0897f06c89310acd'},
{'Automake-1.17_perl_env_space.patch': 'a416eeb854df009f0cdec0484282a3cf7ff6b2637a59e1188932d946625196ab'},
]
builddependencies = [
('binutils', '2.42'),
]
dependencies = [
('Autoconf', '2.72'),
# non-standard Perl modules are required,
# see https://github.com/easybuilders/easybuild-easyconfigs/issues/1822
('Perl', '5.38.2'),
]
preconfigopts = "export PERL='/usr/bin/env perl' && "
sanity_check_paths = {
'files': ['bin/aclocal', 'bin/automake'],
'dirs': []
}
sanity_check_commands = [
"aclocal --help",
"automake --help",
]
moduleclass = 'devel'

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@ -1,52 +0,0 @@
# IT4Innovation
# PH 2025
easyblock = 'ConfigureMake'
name = 'CASTEP'
version = '25.12'
homepage = 'http://www.castep.org'
description = """
CASTEP is an electronic structure materials modelling code based on density
functional theory (DFT), with functionality including geometry optimization
molecular dynamics, phonons, NMR chemical shifts and much more.
"""
toolchain = {'name': 'foss', 'version': '2023b'}
download_instructions = """CASTEP is proprietary software, available under a free-of-charge license for academic use
only. Visit http://www.castep.org and navigate to "Getting Castep" to apply for a license."""
sources = [SOURCE_TAR_GZ]
checksums = ['e21177bfe4cb3f3d098b666c90771e3da2826503b002b8e325e3ca1e230cfc7d']
dependencies = [
('Perl', '5.38.0'),
('Python', '3.11.5'),
('SciPy-bundle', '2023.11'), # for elastic constants and castepconv utility
]
skipsteps = ['configure']
_generic_opts = ' COMMS_ARCH=mpi FFT=fftw3 MATH_LIBS="-lflexiblas" '
buildopts = _generic_opts + 'FFTLIBDIR=$FFT_LIB_DIR MATHLIBDIR=$BLAS_LIB_DIR'
buildopts += ' castep tools utilities'
preinstallopts = 'mkdir -p %(installdir)s/bin &&'
installopts = _generic_opts + 'INSTALL_DIR="%(installdir)s/bin"'
installopts += ' install-castep install-tools install-utilities'
sanity_check_paths = {
'files': ['bin/%s' % x for x in ['castep.mpi', 'optados.mpi', 'orbitals2bands', 'dispersion.pl',
'elastics.py', 'ceteprouts.pm']],
'dirs': [],
}
sanity_check_commands = [
'castep.mpi --help',
'optados.mpi --help',
]
moduleclass = 'phys'

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@ -0,0 +1,64 @@
# IT4Innovation
# PH 2025
easyblock = 'ConfigureMake'
name = 'CASTEP'
version = '25.12'
homepage = 'http://www.castep.org'
description = """CASTEP is an electronic structure materials modelling code based on density functional theory (DFT),
with functionality including geometry optimization molecular dynamics, phonons, NMR chemical shifts and much more."""
toolchain = {'name': 'intel', 'version': '2024a'}
# CASTEP is proprietary software, available under a free-of-charge license for academic use only.
# Visit http://www.castep.org and navigate to "Getting Castep" to apply for a license.
#local_patch_ver = version.split('.')[-1]
import os
if os.environ.get("CLUSTERNAME") in ["KAROLINA"]:
toolchainopts = {'usempi': True, 'openmp': True, 'pic': True, 'lowopt': True, 'optarch': 'march=core-avx2'}
else:
toolchainopts = {'usempi': True, 'openmp': True, 'pic': True}
sources = [SOURCE_TAR_GZ]
checksums = ['e21177bfe4cb3f3d098b666c90771e3da2826503b002b8e325e3ca1e230cfc7d']
# Python and perl really ought to be a dependency for building, running the test suite as well as
# run-time dependencies for various auxiliary utilities.
# In practice the system ones will work fine
dependencies = [
#('Perl', '5.38.0'),
('Python', '3.12.3'),
#('SciPy-bundle', '2024.05', '-gfbf-2024a', True), # for elastic constants and castepconv utility
('imkl', '2024.2.0', '', True),
]
skipsteps = ['configure']
#local_buildopts = 'ARCH=linux_x86_64_gfortran COMMS_ARCH=mpi FFT=mkl MATHLIBS=mkl FFTLIBDIR=$MKLROOT/lib/intel64 MATHLIBDIR=$MKLROOT/lib/intel64'
local_buildopts = 'ARCH=linux_x86_64_ifx COMMS_ARCH=mpi SUBARCH=mpi FFT=mkl MATHLIBS=mkl'
buildopts = local_buildopts + ' castep tools utilities'
preinstallopts = 'mkdir -p %(installdir)s/bin &&'
installopts = local_buildopts + ' INSTALL_DIR="%(installdir)s/bin" install-castep install-tools install-utilities'
sanity_check_paths = {
'files': ['bin/%s' % x for x in ['castep.mpi', 'orbitals2bands', 'dispersion.pl',
'elastics.py', 'ceteprouts.pm']],
'dirs': [],
}
sanity_check_commands = [
'mpirun -n 1 castep.mpi --help',
#'optados.mpi --help',
]
# Run the "quick" set of regression tests
runtest = local_buildopts + ' check-quick'
moduleclass = 'chem'

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@ -0,0 +1,29 @@
# IT4Innovations
# LK 2025
name = 'NCCL'
version = '2.21.5'
versionsuffix = '-CUDA-%(cudaver)s'
homepage = 'https://developer.nvidia.com/nccl'
description = """The NVIDIA Collective Communications Library (NCCL) implements multi-GPU and multi-node collective
communication primitives that are performance optimized for NVIDIA GPUs."""
toolchain = {'name': 'GCCcore', 'version': '14.2.0'}
github_account = 'NVIDIA'
source_urls = [GITHUB_SOURCE]
sources = ['v%(version)s-1.tar.gz']
checksums = ['1923596984d85e310b5b6c52b2c72a1b93da57218f2bc5a5c7ac3d59297a3303']
builddependencies = [('binutils', '2.42')]
dependencies = [
('CUDA', '12.8.0', '', SYSTEM),
('UCX-CUDA', '1.18.0', versionsuffix),
]
# default CUDA compute capabilities to use (override via --cuda-compute-capabilities)
cuda_compute_capabilities = ['8.0']
moduleclass = 'lib'

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@ -33,41 +33,12 @@ dependencies = [
module_add_cuda = False
# specify default CUDA version that should be used by NVHPC
# should match one of the CUDA versions that are included with this NVHPC version
# (see install_components/Linux_x86_64/$version/cuda/) where $version is the NVHPC version
# this version can be tweaked from the EasyBuild command line with
# --try-amend=default_cuda_version="11.0" (for example)
default_cuda_version = '%(cudaver)s'
# NVHPC EasyBlock supports some features, which can be set via CLI or this easyconfig.
# The following list gives examples for the easyconfig
#
# NVHPC needs CUDA to work. Two options are available: 1) Use NVHPC-bundled CUDA, 2) use system CUDA
# 1) Bundled CUDA
# If no easybuild dependency to CUDA is present, the bundled CUDA is taken. A version needs to be specified with
# default_cuda_version = "11.0"
# in this easyconfig file; alternatively, it can be specified through the command line during installation with
# --try-amend=default_cuda_version="10.2"
# 2) CUDA provided via EasyBuild
# Use CUDA as a dependency, for example
# dependencies = [('CUDA', '11.5.0')]
# The parameter default_cuda_version still can be set as above.
# If not set, it will be deduced from the CUDA module (via $EBVERSIONCUDA)
#
# Define a NVHPC-default Compute Capability
# cuda_compute_capabilities = "8.0"
# Can also be specified on the EasyBuild command line via --cuda-compute-capabilities=8.0
# Only single values supported, not lists of values!
#
# Options to add/remove things to/from environment module (defaults shown)
# module_byo_compilers = False # Remove compilers from PATH (Bring-your-own compilers)
# module_nvhpc_own_mpi = False # Add NVHPC's own pre-compiled OpenMPI
# module_add_math_libs = False # Add NVHPC's math libraries (which should be there from CUDA anyway)
# module_add_profilers = False # Add NVHPC's NVIDIA Profilers
# module_add_nccl = False # Add NVHPC's NCCL library
# module_add_nvshmem = False # Add NVHPC's NVSHMEM library
# module_add_cuda = False # Add NVHPC's bundled CUDA
import os
if os.environ.get("CLUSTERNAME") in ["KAROLINA"]:
cuda_compute_capabilities = "8.0"
else:
cuda_compute_capabilities = "7.0"
# this bundle serves as a compiler-only toolchain, so it should be marked as compiler (important for HMNS)
moduleclass = 'compiler'

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@ -0,0 +1,47 @@
# IT4Innovations
# LK 2025
name = 'NVHPC'
version = '25.3'
versionsuffix = '-CUDA-%(cudaver)s'
homepage = 'https://developer.nvidia.com/hpc-sdk/'
description = """C, C++ and Fortran compilers included with the NVIDIA HPC SDK (previously: PGI)"""
toolchain = SYSTEM
local_tarball_tmpl = 'nvhpc_2025_%%(version_major)s%%(version_minor)s_Linux_%s_cuda_multi.tar.gz'
# By downloading, you accept the HPC SDK Software License Agreement
# https://docs.nvidia.com/hpc-sdk/eula/index.html
# accept_eula = True
source_urls = ['https://developer.download.nvidia.com/hpc-sdk/%(version)s/']
sources = [local_tarball_tmpl % '%(arch)s']
checksums = [
{
local_tarball_tmpl % 'aarch64':
'a2b86cf5141c0a9b0925999521693981451a8d2403367c36c46238163be6f2bb',
local_tarball_tmpl % 'x86_64':
'e2b2c911478a5db6a15d1fd258a8c4004dbfccf6f32f4132fe142a24fb7e6f8f',
}
]
local_gccver = '14.2.0'
dependencies = [
('GCCcore', local_gccver),
('binutils', '2.42', '', ('GCCcore', local_gccver)),
# This is necessary to avoid cases where just libnuma.so.1 is present in the system and -lnuma fails
('numactl', '2.0.19', '', ('GCCcore', local_gccver)),
('CUDA', '12.8.0', '', SYSTEM),
]
module_add_cuda = False
default_cuda_version = '%(cudaver)s'
import os
if os.environ.get("CLUSTERNAME") in ["KAROLINA"]:
cuda_compute_capabilities = "8.0"
else:
cuda_compute_capabilities = "7.0"
moduleclass = 'compiler'

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@ -0,0 +1,93 @@
# IT4Innovations
# LK 2025
name = 'OpenMPI'
version = '5.0.7'
homepage = 'https://www.open-mpi.org/'
description = """The Open MPI Project is an open source MPI-3 implementation."""
toolchain = {'name': 'NVHPC', 'version': '25.3-CUDA-12.8.0'}
source_urls = ['https://www.open-mpi.org/software/ompi/v%(version_major_minor)s/downloads']
sources = [SOURCELOWER_TAR_BZ2]
patches = [
('OpenMPI-5.0.7_fix-sshmem-build-failure.patch'),
]
checksums = [
{'openmpi-5.0.7.tar.bz2': '119f2009936a403334d0df3c0d74d5595a32d99497f9b1d41e90019fee2fc2dd'},
{'OpenMPI-5.0.7_fix-sshmem-build-failure.patch':
'7382a5bbe44c6eff9ab05c8f315a8911d529749655126d4375e44e809bfedec7'},
]
builddependencies = [
('pkgconf', '2.3.0'),
('Autotools', '20240712'),
]
dependencies = [
('CUDA', '12.8.0', '', True),
('zlib', '1.3.1'),
('hwloc', '2.11.2'),
('libevent', '2.1.12'),
('UCX', '1.18.0'),
('UCX-CUDA', '1.18.0', '-CUDA-%(cudaver)s'),
('libfabric', '2.0.0'),
('PMIx', '5.0.6'),
('UCC', '1.3.0'),
# ('UCC-CUDA', '1.3.0', '-CUDA-%(cudaver)s'),
('PRRTE', '3.0.8'),
]
# CUDA related patches and custom configure option can be removed if CUDA support isn't wanted.
configopts = '--with-cuda=/usr/local/cuda '
configopts += ' CC=pgcc CXX=pgc++ FC=pgfortran'
configopts += ' CXXFLAGS="-fPIC"'
# IT4I-specific settings
#
#configopts += '--enable-shared '
configopts += ' --enable-mpi-thread-multiple'
configopts += ' --with-verbs'
configopts += ' --enable-mpirun-prefix-by-default'
configopts += ' --with-hwloc=$EBROOTHWLOC' # hwloc support
configopts += ' --with-slurm' # Enable slurm
configopts += ' --with-ucx=$EBROOTUCX'
import os
if os.environ.get("CLUSTERNAME") in ["BARBORA"]:
modextravars = {'OMPI_MCA_btl_openib_if_include': 'mlx5_0',
'OMPI_MCA_btl_tcp_if_include': '10.33.4.0/24',
'OMPI_MCA_orte_base_help_aggregate': '0',
'SLURM_MPI_TYPE': 'pmix_v4',
}
elif os.environ.get("CLUSTERNAME") in ["KAROLINA"]:
modextravars = {'OMPI_MCA_btl_openib_if_include': 'mlx5_0',
'OMPI_MCA_orte_base_help_aggregate': '0',
'SLURM_MPI_TYPE': 'pmix_v4',
}
else:
modextravars = {'OMPI_MCA_btl_openib_if_include': 'mlx4_0',
'OMPI_MCA_oob_tcp_if_include': '10.0.0.0/8',
'SLURM_MPI_TYPE': 'pmix_v4',
}
osdependencies = [('libibverbs-dev', 'libibverbs-devel', 'rdma-core-devel')]
postinstallcmds = [
'echo "# By default, for Open MPI 4.0 and later, infiniband ports on a device are not used by default." >> %(installdir)s/etc/openmpi-mca-params.conf',
'echo "btl_openib_allow_ib = true" >> %(installdir)s/etc/openmpi-mca-params.conf',
]
local_libs = ["mpi_mpifh", "mpi", "ompitrace", "open-pal", "open-rte"]
sanity_check_paths = {
'files': [
"bin/%s" %
binfile for binfile in [
"ompi_info", "opal_wrapper" ]] + [
"include/%s.h" %
x for x in [
"mpi-ext", "mpif-config", "mpif", "mpi", "mpi_portable_platform"]], 'dirs': [], }
moduleclass = 'mpi'

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@ -0,0 +1,69 @@
# IT4Innovations
# LK 2025
name = 'OpenMPI'
version = '5.0.7'
homepage = 'https://www.open-mpi.org/'
description = """The Open MPI Project is an open source MPI-3 implementation."""
toolchain = {'name': 'GCC', 'version': '14.2.0'}
source_urls = ['https://www.open-mpi.org/software/ompi/v%(version_major_minor)s/downloads']
sources = [SOURCELOWER_TAR_BZ2]
patches = [
('OpenMPI-5.0.6_build-with-internal-cuda-header.patch', 1),
('OpenMPI-5.0.7_fix-sshmem-build-failure.patch'),
]
checksums = [
{'openmpi-5.0.7.tar.bz2': '119f2009936a403334d0df3c0d74d5595a32d99497f9b1d41e90019fee2fc2dd'},
{'OpenMPI-5.0.6_build-with-internal-cuda-header.patch':
'4821f0740ae4b97f3ff5259f7bac67a11d8cdeede3b1425825c241cf6a2864bb'},
{'OpenMPI-5.0.7_fix-sshmem-build-failure.patch':
'7382a5bbe44c6eff9ab05c8f315a8911d529749655126d4375e44e809bfedec7'},
]
builddependencies = [
('pkgconf', '2.3.0'),
('Autotools', '20240712'),
]
dependencies = [
('zlib', '1.3.1'),
('hwloc', '2.11.2'),
('libevent', '2.1.12'),
('UCX', '1.18.0'),
('libfabric', '2.0.0'),
('PMIx', '5.0.6'),
('UCC', '1.3.0'),
('PRRTE', '3.0.8'),
]
# CUDA related patches and custom configure option can be removed if CUDA support isn't wanted.
preconfigopts = 'gcc -Iopal/mca/cuda/include -shared opal/mca/cuda/lib/cuda.c -o opal/mca/cuda/lib/libcuda.so && '
configopts = '--with-cuda=%(start_dir)s/opal/mca/cuda --with-show-load-errors=no '
configopts += '--enable-shared --enable-mpi-thread-multiple --with-verbs '
configopts += '--enable-mpirun-prefix-by-default '
configopts += '--with-hwloc=$EBROOTHWLOC ' # hwloc support
configopts += '--with-slurm ' # Enable slurm
configopts += '--with-ucx=$EBROOTUCX '
import os
if os.environ.get("CLUSTERNAME") in ["BARBORA"]:
modextravars = {'OMPI_MCA_btl_openib_if_include': 'mlx5_0',
'OMPI_MCA_btl_tcp_if_include': '10.33.4.0/24',
'OMPI_MCA_orte_base_help_aggregate': '0',
'SLURM_MPI_TYPE': 'pmix_v4',
}
elif os.environ.get("CLUSTERNAME") in ["KAROLINA"]:
modextravars = {'OMPI_MCA_btl_openib_if_include': 'mlx5_0',
'OMPI_MCA_orte_base_help_aggregate': '0',
'SLURM_MPI_TYPE': 'pmix_v4',
}
else:
modextravars = {'OMPI_MCA_btl_openib_if_include': 'mlx4_0',
'OMPI_MCA_oob_tcp_if_include': '10.0.0.0/8',
'SLURM_MPI_TYPE': 'pmix_v4',
}
moduleclass = 'mpi'

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@ -0,0 +1,59 @@
# IT4Innovations
# LK 2025
easyblock = 'ConfigureMake'
name = 'UCC-CUDA'
version = '1.3.0'
versionsuffix = '-CUDA-%(cudaver)s'
homepage = 'https://www.openucx.org/'
description = """UCC (Unified Collective Communication) is a collective
communication operations API and library that is flexible, complete, and
feature-rich for current and emerging programming models and runtimes.
This module adds the UCC CUDA support.
"""
toolchain = {'name': 'GCCcore', 'version': '14.2.0'}
toolchainopts = {'pic': True}
source_urls = ['https://github.com/openucx/ucc/archive/refs/tags']
sources = ['v%(version)s.tar.gz']
#patches = [
# '%(name)s-1.3.0_link_against_existing_UCC_libs.patch',
# '%(name)s-1.3.0_cuda_12_mem_ops.patch',
#]
checksums = [
{'v1.3.0.tar.gz': 'b56379abe5f1c125bfa83be305d78d81a64aa271b7b5fff0ac17b86725ff3acf'},
{'UCC-CUDA-1.3.0_link_against_existing_UCC_libs.patch': '328e0f7e4de76a9dc6ecc07427581df661c27f6c0ace24f49a7b3289a39777c7'},
{'UCC-CUDA-1.3.0_cuda_12_mem_ops.patch': 'fc3ea1487d29dc626db2363ef5a79e7f0906f6a7507a363fa6167a812b143eb6'},
]
builddependencies = [
('binutils', '2.42'),
('Autotools', '20240712'),
]
dependencies = [
('UCC', '1.3.0'),
('CUDA', '12.8.0', '', SYSTEM),
('UCX-CUDA', '1.18.0', '-CUDA-%(cudaver)s'),
('NCCL', '2.21.5', '-CUDA-%(cudaver)s'),
]
preconfigopts = "./autogen.sh && "
buildopts = '-C src/components/mc/cuda V=1 && make -C src/components/tl/nccl V=1'
installopts = '-C src/components/mc/cuda && make -C src/components/tl/nccl install'
sanity_check_paths = {
'files': ['lib/ucc/libucc_mc_cuda.%s' % SHLIB_EXT, 'lib/ucc/libucc_tl_nccl.%s' % SHLIB_EXT],
'dirs': ['lib']
}
sanity_check_commands = ["ucc_info -c"]
modextrapaths = {'EB_UCC_EXTRA_COMPONENT_PATH': 'lib/ucc'}
moduleclass = 'lib'

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@ -1,44 +0,0 @@
# IT4Innovations
# LK 2024
easyblock = 'ConfigureMake'
name = 'UCC'
version = '1.3.0'
homepage = 'https://www.openucx.org/'
description = """UCC (Unified Collective Communication) is a collective
communication operations API and library that is flexible, complete, and
feature-rich for current and emerging programming models and runtimes.
"""
toolchain = {'name': 'GCCcore', 'version': '14.2.0'}
toolchainopts = {'pic': True}
source_urls = ['https://github.com/openucx/ucc/archive/refs/tags']
sources = ['v%(version)s.tar.gz']
patches = ['UCC-1.1.0-multiple_component_paths.patch']
checksums = [
{'v1.3.0.tar.gz': 'b56379abe5f1c125bfa83be305d78d81a64aa271b7b5fff0ac17b86725ff3acf'},
{'UCC-1.1.0-multiple_component_paths.patch': '3081d0f694331daa4a88a0fa3fb54b9a918015248ae5eb7b3157b924abd31bee'},
]
builddependencies = [
('binutils', '2.42'),
('Autotools', '20231222'),
]
dependencies = [
('UCX', '1.16.0'),
]
preconfigopts = "./autogen.sh && "
sanity_check_paths = {
'files': ['bin/ucc_info'],
'dirs': ['include', 'lib']
}
sanity_check_commands = ["ucc_info -c"]
moduleclass = 'lib'

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@ -0,0 +1,64 @@
--- arch/makefile.include.nvhpc_acc.orig 2025-04-09 12:20:02.277358084 +0200
+++ arch/makefile.include.nvhpc_acc 2025-04-09 12:22:34.890663227 +0200
@@ -17,8 +17,8 @@
# N.B.: you might need to change the cuda-version here
# to one that comes with your NVIDIA-HPC SDK
CC = mpicc -acc -gpu=cc60,cc70,cc80,cuda11.8
-FC = mpif90 -acc -gpu=cc60,cc70,cc80,cuda11.8
-FCL = mpif90 -acc -gpu=cc60,cc70,cc80,cuda11.8 -c++libs
+FC = mpif90 -acc -gpu=cc60,cc70,cc80,cuda12.3
+FCL = mpif90 -acc -gpu=cc60,cc70,cc80,cuda12.3 -c++libs
FREE = -Mfree
@@ -59,19 +59,19 @@
# Specify your NV HPC-SDK installation (mandatory)
#... first try to set it automatically
-NVROOT =$(shell which nvfortran | awk -F /compilers/bin/nvfortran '{ print $$1 }')
+#NVROOT =$(shell which nvfortran | awk -F /compilers/bin/nvfortran '{ print $$1 }')
# If the above fails, then NVROOT needs to be set manually
-#NVHPC ?= /opt/nvidia/hpc_sdk
-#NVVERSION = 21.11
-#NVROOT = $(NVHPC)/Linux_x86_64/$(NVVERSION)
+NVHPC ?= ${EBROOTQD}
+NVVERSION = ${EBVERSIONNVHPC}
+NVROOT = $(NVHPC)/Linux_x86_64/$(NVVERSION)
## Improves performance when using NV HPC-SDK >=21.11 and CUDA >11.2
-#OFLAG_IN = -fast -Mwarperf
-#SOURCE_IN := nonlr.o
+OFLAG_IN = -fast -Mwarperf
+SOURCE_IN := nonlr.o
# Software emulation of quadruple precsion (mandatory)
-QD ?= $(NVROOT)/compilers/extras/qd
+QD ?= ${EBROOTQD}
LLIBS += -L$(QD)/lib -lqdmod -lqd
INCS += -I$(QD)/include/qd
@@ -87,7 +87,7 @@
LLIBS += $(SCALAPACK) $(LAPACK) $(BLAS)
# FFTW (mandatory)
-FFTW_ROOT ?= /path/to/your/fftw/installation
+FFTW_ROOT ?= ${EBROOTFFTWMPI}
LLIBS += -L$(FFTW_ROOT)/lib -lfftw3
INCS += -I$(FFTW_ROOT)/include
@@ -97,10 +97,10 @@
#LLIBS += -cudalib=cusolvermp,cublasmp -lnvhpcwrapcal
# HDF5-support (optional but strongly recommended, and mandatory for some features)
-#CPP_OPTIONS+= -DVASP_HDF5
-#HDF5_ROOT ?= /path/to/your/hdf5/installation
-#LLIBS += -L$(HDF5_ROOT)/lib -lhdf5_fortran
-#INCS += -I$(HDF5_ROOT)/include
+CPP_OPTIONS+= -DVASP_HDF5
+HDF5_ROOT ?= ${EBROOTHDF5}
+LLIBS += -L$(HDF5_ROOT)/lib -lhdf5_fortran
+INCS += -I$(HDF5_ROOT)/include
# For the VASP-2-Wannier90 interface (optional)
#CPP_OPTIONS += -DVASP2WANNIER90

View File

@ -0,0 +1,80 @@
# IT4Innovations
# LK 2025
easyblock = 'MakeCp'
name = 'VASP'
version = '6.5.1'
local_cudaversion = '12.3.0'
versionsuffix = '-CUDA-%s' % local_cudaversion
homepage = 'https://www.vasp.at'
docurls = 'https://www.vasp.at/wiki/index.php/The_VASP_Manual'
description = """
The Vienna Ab initio Simulation Package (VASP) is a local computer program for atomic scale
materials modelling, e.g. electronic structure calculations and quantum-mechanical molecular dynamics,
from first principles.
This is a GPU-enabled build.
To use VASP, you need an academic license from University of Vienna.
Follow the instructions at https://www.vasp.at/index.php/faqs.
Please send us the ID of your VASP license, list of authorized users for whom you require access,
and their email which is associated with your license (use only https://support.it4i.cz/rt).
We are responsible for verifying your licenses.
"""
toolchain = {'name': 'NVHPC', 'version': '24.3-CUDA-12.3.0'}
toolchainopts = {'pic': True}
# Vasp is proprietary software, see http://www.vasp.at/index.php/faqs on
# how to get access to the code
sources = ['%(namelower)s.%(version)s.tgz']
patches = ['VASP-%(version)s-NVHPC-24.3-CUDA-12.3.0-adjust-makefile.patch']
checksums = [
{'vasp.%(version)s.tgz': 'a53fd9dd2a66472a4aa30074dbda44634fc663ea2628377fc01d870e37136f61'},
{'VASP-%(version)s-NVHPC-24.3-CUDA-12.3.0-adjust-makefile.patch': '80c166c2039ea83e00291091b77ec013adfc4b0e09d9cb1b71ef73bdaa56df96'},
]
dependencies = [
('OpenMPI', '4.1.6'),
('FFTW.MPI', '3.3.10'),
('FFTW', '3.3.10'),
('imkl', '2022.2.1', '', True),
('ScaLAPACK', '3.0'),
('HDF5', '1.14.3'),
('QD', '2.3.17'),
]
prebuildopts = 'cp arch/makefile.include.nvhpc_acc ./makefile.include && '
# VASP uses LIBS as a list of folders
prebuildopts += 'unset LIBS && '
# AMD/Intel CPU switch - We set xHost by default; change it to -march=core-avx2 when necessary
import os
if os.environ.get("CLUSTERNAME") in ["KAROLINA"]:
prebuildopts += 'sed -i "s|-xHOST|-march=core-avx2|" makefile.include && '
prebuildopts += 'sed -i "s|-march=xHost|-march=core-avx2|" makefile.include && '
prebuildopts += 'sed -i "s|cuda12.1|cuda12.3|g" makefile.include && '
buildopts = 'std gam ncl '
parallel = 1
files_to_copy = [(['bin/vasp_std', 'bin/vasp_gam', 'bin/vasp_ncl'], 'bin')]
sanity_check_paths = {
'files': ['bin/vasp_std', 'bin/vasp_gam', 'bin/vasp_ncl'],
'dirs': []
}
modluafooter = """
add_property('state','license')
add_property('arch', 'gpu')
"""
moduleclass = 'chem'

View File

@ -0,0 +1,65 @@
# IT4Innovations
# LK 2025
easyblock = 'MakeCp'
name = 'VASP'
version = '6.5.1'
homepage = 'http://www.vasp.at'
docurls = 'https://www.vasp.at/wiki/index.php/The_VASP_Manual'
description = """The Vienna Ab initio Simulation Package (VASP) is a local computer program for atomic scale
materials modelling, e.g. electronic structure calculations and quantum-mechanical molecular dynamics,
from first principles.
To use VASP, you need an academic license from University of Vienna. Follow the instructions at https://www.vasp.at/index.php/faqs.
Please send us a list of authorized users and their IDs for which you need access (use only http://support.it4i.cz/rt). We are responsible for verifying your licenses."""
toolchain = {'name': 'intel', 'version': '2024a'}
# Vasp is proprietary software, see http://www.vasp.at/index.php/faqs on
# how to get access to the code
sources = ['%(namelower)s.%(version)s.tgz']
patches = ['VASP-%(version)s-intel-hdf5.patch']
checksums = [
{'vasp.%(version)s.tgz': 'a53fd9dd2a66472a4aa30074dbda44634fc663ea2628377fc01d870e37136f61'},
{'VASP-%(version)s-intel-hdf5.patch': '1289ed84508c9e655ba00da623231e48cd773edda1344bdf3ea13e08ae910d9b'},
]
# use serial compilation of W90, see https://www.vasp.at/wiki/index.php/Makefile.include#Wannier90_.28optional.29
# Important: In case of Wannier90 3.x, you should compile a serial version by removing COMMS=mpi in the make.inc of Wannier90.
dependencies = [
('HDF5', '1.14.3'),
('Wannier90', '3.1.0', '-serial'),
]
prebuildopts = 'cp arch/makefile.include.intel ./makefile.include && '
# AMD/Intel CPU switch - We set xHost by default; change it to -march=core-avx2 when necessary
import os
if os.environ.get("CLUSTERNAME") in ["KAROLINA"]:
prebuildopts += 'sed -i "s|-xHOST|-march=core-avx2|" makefile.include && '
prebuildopts += 'sed -i "s|-march=xHost|-march=core-avx2|" makefile.include && '
# Fix icc vs icx
prebuildopts += 'sed -i "s|CC_LIB = icc|CC_LIB = icx|" makefile.include && '
# Fix icpc vs icpx
prebuildopts += 'sed -i "s|CXX_PARS = icpc|CXX_PARS = icpx|" makefile.include && '
# VASP uses LIBS as a list of folders
prebuildopts += 'unset LIBS && '
buildopts = 'std gam ncl '
max_parallel = 1
files_to_copy = [(['bin/vasp_std', 'bin/vasp_gam', 'bin/vasp_ncl'], 'bin')]
sanity_check_paths = {
'files': ['bin/vasp_std', 'bin/vasp_gam', 'bin/vasp_ncl'],
'dirs': []
}
modluafooter = 'add_property("state","license")'
moduleclass = 'chem'

View File

@ -0,0 +1,31 @@
--- arch/makefile.include.intel.orig 2025-04-09 10:56:34.041874570 +0200
+++ arch/makefile.include.intel 2025-04-09 10:58:31.197543756 +0200
@@ -49,20 +49,20 @@
# Intel MKL (FFTW, BLAS, LAPACK, and scaLAPACK)
# (Note: for Intel Parallel Studio's MKL use -mkl instead of -qmkl)
FCL += -qmkl=sequential
-MKLROOT ?= /path/to/your/mkl/installation
+MKLROOT ?= ${MKLROOT}
LLIBS += -L$(MKLROOT)/lib/intel64 -lmkl_scalapack_lp64 -lmkl_blacs_intelmpi_lp64
INCS =-I$(MKLROOT)/include/fftw
# HDF5-support (optional but strongly recommended, and mandatory for some features)
-#CPP_OPTIONS+= -DVASP_HDF5
-#HDF5_ROOT ?= /path/to/your/hdf5/installation
-#LLIBS += -L$(HDF5_ROOT)/lib -lhdf5_fortran
-#INCS += -I$(HDF5_ROOT)/include
+CPP_OPTIONS+= -DVASP_HDF5
+HDF5_ROOT ?= ${EBROOTHDF5}
+LLIBS += -L$(HDF5_ROOT)/lib -lhdf5_fortran
+INCS += -I$(HDF5_ROOT)/include
# For the VASP-2-Wannier90 interface (optional)
-#CPP_OPTIONS += -DVASP2WANNIER90
-#WANNIER90_ROOT ?= /path/to/your/wannier90/installation
-#LLIBS += -L$(WANNIER90_ROOT)/lib -lwannier
+CPP_OPTIONS += -DVASP2WANNIER90
+WANNIER90_ROOT ?= {EBROOTWANNIER90}
+LLIBS += -L$(WANNIER90_ROOT)/lib -lwannier
# For machine learning library vaspml (experimental)
#CPP_OPTIONS += -Dlibvaspml