[SuiteSparse] [package list]

SuiteSparse/5.13.0-cpeAOCC-24.03-OpenMP (SuiteSparse-5.13.0-cpeAOCC-24.03-OpenMP.eb)

To access module help and find out for which stacks and partitions the module is installed, use module spider SuiteSparse/5.13.0-cpeAOCC-24.03-OpenMP.

EasyConfig:

easyblock = 'ConfigureMake'

local_metis_version       = '5.1.0'
local_MPFR_version        = '4.2.0'
local_SuiteSparse_version = '5.13.0'

name = 'SuiteSparse'
version = local_SuiteSparse_version
versionsuffix = '-OpenMP'

homepage = 'https://faculty.cse.tamu.edu/davis/suitesparse.html'

whatis = ['Description: SuiteSparse is a collection of libraries to manipulate sparse matrices.']

description = """
SuiteSparse is a suite of sparse matrix algorithms. This package include:

  - AMD       : approximate minimum degree ordering
  - BTF       : permutation to block triangular form
  - CAMD      : constrained approximate minimum degree ordering
  - CCOLAMD   : constrained column approximate minimum degree ordering
  - CHOLMOD   : sparse Cholesky factorization
  - COLAMD    : column approximate minimum degree ordering
  - CXSparse  : CSparse Extended, includes support for complex matrices
  - KLU       : parse LU factorization, primarily for circuit simulation
  - LDL       : a very concise LDL' factorization package
  - RBio      : read/write sparse matrices in Rutherford/Boeing format
  - SPQR      : sparse QR factorization.
  - UMFPACK   : sparse LU factorization
"""

toolchain = {'name': 'cpeAOCC', 'version': '24.03'}
toolchainopts = {'unroll': True, 'pic': True, 'openmp': True}

source_urls = ['https://github.com/DrTimothyAldenDavis/SuiteSparse/archive']
sources = ['v%(version)s.tar.gz']
checksums = ['59c6ca2959623f0c69226cf9afb9a018d12a37fab3a8869db5f6d7f83b6b147d']

builddependencies = [
    ('buildtools',          '%(toolchain_version)s', '', True),
    ('craype-network-none', EXTERNAL_MODULE),
    ('craype-accel-host',   EXTERNAL_MODULE),
]

dependencies = [
    ('METIS', local_metis_version),
    ('MPFR',  local_MPFR_version),
]

skipsteps = ['configure']

prebuildopts = ' && '.join([
    'export LD_LIBRARY_PATH=%(builddir)s/SuiteSparse-%(version)s/lib:$LD_LIBRARY_PATH',
    'export CMAKE_OPTIONS="-DCMAKE_INSTALL_PREFIX=%(installdir)s"',
    'rm -f GraphBLAS/CUDA/test/graphblascuda_test',
    'module unload xpmem',
]) + ' && '


# Make sure we only link the multithreaded variant of libsci
prebuildopts += 'LDFLAGS="-fopenmp" '
preinstallopts = prebuildopts

local_commonopts = ' '.join([
    'BLAS="" LAPACK=""',
    'MY_METIS_LIB="$EBROOTMETIS/lib/libmetis.%s"' % SHLIB_EXT,
    'MY_METIS_INC="$EBROOTMETIS/include"',
]) + ' '

buildopts = local_commonopts
installopts = local_commonopts + 'INSTALL="%(installdir)s"'

postinstallcmds = [
    'mkdir -p %(installdir)s/share/licenses/%(name)s',
    'cd ../%(name)s-%(version)s && cp LICENSE.txt CITATION.bib %(installdir)s/share/licenses/%(name)s',
]

local_libnames = [
    'AMD', 'BTF', 'CAMD', 'CCOLAMD', 'CHOLMOD', 'COLAMD', 
    'CXSparse', 'KLU', 'LDL', 'RBio', 'SPQR', 'UMFPACK'
]

sanity_check_paths = {
    'files': [
        'lib/lib%s.%s' % (lib.lower(), SHLIB_EXT) for lib in local_libnames 
    ],
    'dirs': []
}

moduleclass = 'numlib'

[SuiteSparse] [package list]