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new file: f/funcsigs/funcsigs-1.0.2-Py-3.6.eb modified: g/GDAL/GDAL-2.3.2-Py-2.7.eb new file: h/hwloc/hwloc-1.11.7-c7.eb new file: k/Keras_Applications/Keras_Applications-1.0.6-Py-3.6.eb new file: k/Keras_Preprocessing/Keras_Preprocessing-1.0.5-Py-3.6.eb new file: m/mock/mock-2.0.0-Py-3.6.eb new file: n/numactl/numactl-2.0.11-c7.eb new file: n/numpy/numpy-1.15.4-Py-3.6.eb modified: o/OpenMPI/OpenMPI-1.10.7-PGI-18.5-GCC-6.3.0-2.27.eb new file: o/OpenMPI/OpenMPI-2.1.1-c7.eb new file: p/pbr/pbr-5.1.1-Py-3.6.eb new file: p/protobuf-python/protobuf-python-3.6.1-Py-3.6.eb new file: p/protobuf/protobuf-3.6.1-Py-3.6.eb new file: r/RDKit/RDKit-2018.09.1-foss-2017a-Py-2.7.eb new file: t/Tensorflow/Tensorflow-1.12.0-GCC-6.3.0-2.27-Py-3.6.eb
34 lines
921 B
Plaintext
34 lines
921 B
Plaintext
# IT4Innovations 2018
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easyblock = 'ConfigureMake'
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name = 'numactl'
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version = '2.0.11'
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versionsuffix= '-c7'
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homepage = 'http://oss.sgi.com/projects/libnuma/'
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description = """The numactl program allows you to run your application program on specific cpu's and memory nodes.
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It does this by supplying a NUMA memory policy to the operating system before running your program.
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The libnuma library provides convenient ways for you to add NUMA memory policies into your own program."""
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toolchain = {'name': 'dummy', 'version': ''}
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toolchainopts = {'pic': True}
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source_urls = ['https://github.com/numactl/numactl/archive/']
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sources = [SOURCE_TAR_GZ]
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#preconfigopts = "./autogen.sh && "
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sanity_check_paths = {
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'files': [
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'bin/numactl',
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'bin/numastat',
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'lib/libnuma.%s' %
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SHLIB_EXT,
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'lib/libnuma.a'],
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'dirs': [
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'share/man',
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'include']}
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moduleclass = 'tools'
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