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new file: c/CubeGUI/CubeGUI-4.4.3-gompi-2019.02.eb new file: c/CubeLib/CubeLib-4.4.3-gompi-2019.02.eb new file: c/CubeW/CubeW-4.4.2-gompi-2019.02.eb new file: m/MVAPICH2/MVAPICH2-2.3-GCC-6.3.0-2.27.eb new file: p/ParMETIS/ParMETIS-4.0.3-foss-2018a.eb new file: s/Scalasca/Scalasca-2.5-gompi-2019.02.eb new file: s/Scalasca/Scalasca-2.5-gompi-2019.03.eb new file: s/Scalasca/Scalasca-2.5-intel-2017a.eb new file: s/Scalasca/Scalasca-2.5-intel-2018a.eb new file: s/Score-P/Score-P-5.0-gompi-2019.02.eb new file: s/SuiteSparse/SuiteSparse-5.4.0-foss-2018a-METIS-5.1.0.eb new file: t/Trilinos/Trilinos-12.12.1-foss-2018a-Py-2.7.eb new file: t/Trilinos/Trilinos-12.14.1-foss-2018a-Py-2.7.eb modified: t/Trilinos/Trilinos-12.14.1-intel-2017c-Py-2.7.eb deleted: s/Score-P/Score-P-5.0-intel-2019.02.eb
25 lines
1.0 KiB
Plaintext
25 lines
1.0 KiB
Plaintext
# IT4Innovations 2019
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name = 'ParMETIS'
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version = '4.0.3'
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homepage = 'http://glaros.dtc.umn.edu/gkhome/metis/parmetis/overview'
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description = """ParMETIS is an MPI-based parallel library that implements a variety of algorithms for partitioning unstructured graphs,
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meshes, and for computing fill-reducing orderings of sparse matrices. ParMETIS extends the functionality provided by METIS and includes
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routines that are especially suited for parallel AMR computations and large scale numerical simulations. The algorithms implemented in
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ParMETIS are based on the parallel multilevel k-way graph-partitioning, adaptive repartitioning, and parallel multi-constrained partitioning
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schemes."""
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toolchain = {'name': 'foss', 'version': '2018a'}
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toolchainopts = {'usempi': True, 'pic': True}
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source_urls = [
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'http://glaros.dtc.umn.edu/gkhome/fetch/sw/parmetis',
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'http://glaros.dtc.umn.edu/gkhome/fetch/sw/parmetis/OLD',
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]
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sources = [SOURCELOWER_TAR_GZ]
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builddependencies = [('CMake', '3.13.1', '', True)]
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moduleclass = 'math'
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