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new file: e/ELSI/ELSI-2.5.0-intel-2020b.eb new file: f/FFTW/FFTW-3.3.8-gompi-2020a-amd.eb new file: l/libGridXC/libGridXC-0.8.5-iimpi-2020b.eb new file: l/libPSML/libPSML-1.1.8-iccifort-2020.4.304.eb new file: l/libxc/libxc-4.3.4-intel-2020b.eb new file: p/PETSc/PETSc-3.12.4-intel-2020b.eb new file: s/SLEPc/SLEPc-3.13.3-intel-2020a-Python-3.8.6.eb new file: s/Siesta/Siesta-4.1-Max-1.2.0-intel-2020b.eb new file: s/Siesta/Siesta-4.1-b5-intel-2020b-test.eb new file: t/TotalView/TotalView-2021.2.14.eb new file: x/xmlf90/xmlf90-1.5.4-iccifort-2020.4.304.eb
29 lines
1002 B
Plaintext
29 lines
1002 B
Plaintext
# IT4Innovations
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# LK 2021
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name = 'SLEPc'
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version = '3.13.3'
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versionsuffix = '-Python-%(pyver)s'
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homepage = 'https://slepc.upv.es/'
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description = """SLEPc (Scalable Library for Eigenvalue Problem Computations) is a software library for the solution
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of large scale sparse eigenvalue problems on parallel computers. It is an extension of PETSc and can be used for
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either standard or generalized eigenproblems, with real or complex arithmetic. It can also be used for computing a
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partial SVD of a large, sparse, rectangular matrix, and to solve quadratic eigenvalue problems."""
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toolchain = {'name': 'intel', 'version': '2020b'}
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toolchainopts = {'usempi': True, 'openmp': True}
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source_urls = ['https://slepc.upv.es/download/distrib']
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sources = [SOURCELOWER_TAR_GZ]
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checksums = ['a586ce572a928ed87f04961850992a9b8e741677397cbaa3fb028323eddf4598']
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dependencies = [
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('Python', '3.8.6'),
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('PETSc', '3.12.4', versionsuffix),
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]
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petsc_arch = 'installed-arch-linux-c-opt'
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moduleclass = 'numlib'
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