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modified: b/Boost/Boost-1.77.0-gompi-2021a.eb modified: c/CMake/CMake-3.16.2.eb new file: e/ELPA/ELPA-2019.11.001-intel-2021a.eb modified: e/ELPA/ELPA-2023.11.001-intel-2023b.eb modified: h/HDF5/HDF5-1.10.6-intel-2020a.eb modified: i/IOTK/IOTK-1.2.2-intel-2020a.eb modified: j/Java/Java-1.8.0_221.eb modified: n/NVHPC/NVHPC-21.9.eb modified: n/netCDF-Fortran/netCDF-Fortran-4.5.2-intel-2020a.eb modified: n/netCDF/netCDF-4.7.3-intel-2020a.eb new file: p/PETSc/PETSc-3.21.2-foss-2022b.eb new file: p/petsc4py/petsc4py-3.21.2-foss-2022b.eb modified: q/QMCPACK/QMCPACK-3.14.0-foss-2021a-Python-3.9.5.eb new file: q/QuantumESPRESSO/QuantumESPRESSO-6.7-intel-2020a-MaX.eb new file: q/QuantumESPRESSO/QuantumESPRESSO-7.2-intel-2021a.eb new file: q/QuantumESPRESSO/QuantumESPRESSO-7.3-intel-2021a.eb new file: q/QuantumESPRESSO/QuantumESPRESSO-7.3.1-intel-2023b-gpu.eb new file: s/SLEPc/SLEPc-3.21.1-foss-2022b.eb new file: s/slepc4py/slepc4py-3.21.1-foss-2022b.eb new file: s/sqsgenerator/sqsgenerator-0.3-conda.eb modified: s/sqsgenerator/sqsgenerator-0.3-foss-2023b-Python-3.11.5.eb new file: y/Yambo/Yambo-5.2.3-intel-2020a.eb
67 lines
3.1 KiB
Plaintext
67 lines
3.1 KiB
Plaintext
# IT4Innovations 2021
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# LK
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name = 'NVHPC'
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version = '21.9'
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homepage = 'https://developer.nvidia.com/hpc-sdk/'
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description = """C, C++ and Fortran compilers included with the NVIDIA HPC SDK (previously: PGI)"""
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toolchain = SYSTEM
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# By downloading, you accept the HPC SDK Software License Agreement (https://docs.nvidia.com/hpc-sdk/eula/index.html)
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accept_eula = True
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source_urls = ['https://developer.download.nvidia.com/hpc-sdk/%(version)s/']
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local_tarball_tmpl = 'nvhpc_2021_%%(version_major)s%%(version_minor)s_Linux_%s_cuda_multi.tar.gz'
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sources = [local_tarball_tmpl % '%(arch)s']
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checksums = ['7de6a6880fd7e59afe0dee51f1fae4d3bff1ca0fb8ee234b24e1f2fdff23ffc9']
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#local_gccver = '10.2.0'
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#dependencies = [
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# ('GCCcore', local_gccver),
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# ('binutils', '2.35', '', ('GCCcore', local_gccver)),
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# This is necessary to avoid cases where just libnuma.so.1 is present in the system and -lnuma fails
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# ('numactl', '2.0.13', '', ('GCCcore', local_gccver))
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#]
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# specify default CUDA version that should be used by NVHPC
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# should match one of the CUDA versions that are included with this NVHPC version
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# (see install_components/Linux_x86_64/20.7/cuda/)
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# for NVHPC 20.7, those are: 11.0, 10.2, 10.1;
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# this version can be tweaked from the EasyBuild command line with
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# --try-amend=default_cuda_version="10.2" (for example)
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default_cuda_version = '11.4'
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# NVHPC EasyBlock supports some features, which can be set via CLI or this easyconfig.
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# The following list gives examples for the easyconfig
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#
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# NVHPC needs CUDA to work. Two options are available: 1) Use NVHPC-bundled CUDA, 2) use system CUDA
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# 1) Bundled CUDA
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# If no easybuild dependency to CUDA is present, the bundled CUDA is taken. A version needs to be specified with
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# default_cuda_version = "11.0"
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# in this easyconfig file; alternatively, it can be specified through the command line during installation with
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# --try-amend=default_cuda_version="10.2"
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# 2) CUDA provided via EasyBuild
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# Use CUDAcore as a dependency, for example
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# dependencies = [('CUDAcore', '11.0.2')]
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# The parameter default_cuda_version still can be set as above.
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# If not set, it will be deduced from the CUDA module (via $EBVERSIONCUDA)
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#
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# Define a NVHPC-default Compute Capability
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# cuda_compute_capabilities = "8.0"
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cuda_compute_capabilities = '7.0' #V100 GPU
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# Can also be specified on the EasyBuild command line via --cuda-compute-capabilities=8.0
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# Only single values supported, not lists of values!
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#
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# Options to add/remove things to/from environment module (defaults shown)
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# module_byo_compilers = Yes # Remove compilers from PATH (Bring-your-own compilers)
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# module_nvhpc_own_mpi = False # Add NVHPC's own pre-compiled OpenMPI
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# module_add_math_libs = Yes # Add NVHPC's math libraries (which should be there from CUDA anyway)
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# module_add_profilers = Yes # Add NVHPC's NVIDIA Profilers
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# module_add_nccl = Yes # Add NVHPC's NCCL library
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# module_add_nvshmem = Yes # Add NVHPC's NVSHMEM library
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# module_add_cuda = Yes # Add NVHPC's bundled CUDA
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# this bundle serves as a compiler-only toolchain, so it should be marked as compiler (important for HMNS)
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moduleclass = 'compiler'
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