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new file: a/alchemlyb/alchemlyb-0.1.0-Py-2.7.eb new file: g/gperftools/gperftools-2.7.eb new file: h/HDF5/HDF5-1.10.4-gompi-2019.02-parallel.eb new file: h/HDF5/HDF5-1.10.4-intel-2018a-parallel.eb new file: h/h5py/h5py-2.9.0-intel-2018a-Py-2.7.eb new file: l/LAMMPS/LAMMPS-20181212-intel-2017c.eb new file: m/mpi4py/mpi4py-3.0.0-intel-2018a-Py-2.7.eb new file: p/pandas/pandas-0.23.4-Py-2.7.eb new file: p/pkgconfig/pkgconfig-1.3.1-intel-2018a-Py-2.7.eb new file: p/pmx/pmx-20190115-Py-2.7.eb new file: p/pymbar/pymbar-3.0.3-Py-2.7.eb new file: p/pytz/pytz-2018.9-Py-2.7.eb modified: q/QMCPACK/QMCPACK-3.6.0-intel-2018a.eb new file: s/scikit-learn/scikit-learn-0.20.2-Py-2.7.eb new file: t/tbb/tbb-2018_U5-intel-2017c.eb modified: x/X11/X11-20170314.eb
21 lines
626 B
Plaintext
21 lines
626 B
Plaintext
# IT4Innovations 2019
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name = 'tbb'
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version = '2018_U5'
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homepage = 'https://01.org/tbb/'
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description = """Intel(R) Threading Building Blocks (Intel(R) TBB) lets you easily write parallel C++ programs that
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take full advantage of multicore performance, that are portable, composable and have future-proof scalability."""
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toolchain = {'name': 'intel', 'version': '2017c'}
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source_urls = ['https://github.com/01org/tbb/archive/']
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sources = ['%(version)s.tar.gz']
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checksums = ['c4c2896af527392496c5e01ef8579058a71b6eebbd695924cd138841c13f07be']
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builddependencies = [
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('binutils', '2.31.1', '', True)
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]
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moduleclass = 'lib'
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