94 lines
3.4 KiB
Python
94 lines
3.4 KiB
Python
# Copyright 2013-2020 Lawrence Livermore National Security, LLC and other
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# Spack Project Developers. See the top-level COPYRIGHT file for details.
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#
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# SPDX-License-Identifier: (Apache-2.0 OR MIT)
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from spack import *
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class Blaspp(CMakePackage, CudaPackage):
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"""C++ API for the Basic Linear Algebra Subroutines. Developed by the
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Innovative Computing Laboratory at the University of Tennessee,
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Knoxville."""
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homepage = "https://bitbucket.org/icl/blaspp"
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git = "https://bitbucket.org/icl/blaspp"
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maintainers = ['teonnik', 'Sely85', 'G-Ragghianti', 'mgates3']
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version('develop', commit='6293d96')
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variant('gfort',
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default=False,
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description=('Use GNU Fortran interface. '
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'Default is Intel interface. (MKL)'))
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variant('ilp64',
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default=False,
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description=('Use 64bit integer interface. '
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'Default is 32bit. (MKL & ESSL)'))
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variant('openmp',
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default=False,
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description=('Use OpenMP threaded backend. '
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'Default is sequential. (MKL & ESSL)'))
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depends_on('blas')
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# 1) The CMake options exposed by `blaspp` allow for a value called `auto`.
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# The value is not needed here as the choice of dependency in the spec
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# determines the appropriate flags.
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#
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# 2) BLASFinder.cmake handles most options. For `auto`, it searches all
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# blas libraries listed in `def_lib_list`.
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#
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# 3) ?? Custom blas library can be supplied via `BLAS_LIBRARIES`.
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#
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def cmake_args(self):
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spec = self.spec
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args = ['-DBLASPP_BUILD_TESTS:BOOL={0}'.format(
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'ON' if self.run_tests else 'OFF')]
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if '+gfort' in spec:
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args.append('-DBLAS_LIBRARY_MKL="GNU gfortran conventions"')
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else:
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args.append('-DBLAS_LIBRARY_MKL="Intel ifort conventions"')
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if '+ilp64' in spec:
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args.append('-DBLAS_LIBRARY_INTEGER="int64_t (ILP64)"')
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else:
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args.append('-DBLAS_LIBRARY_INTEGER="int (LP64)"')
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if '+openmp' in spec:
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args.append(['-DUSE_OPENMP=ON',
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'-DBLAS_LIBRARY_THREADING="threaded"'])
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else:
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args.append('-DBLAS_LIBRARY_THREADING="sequential"')
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# `blaspp` has an implicit CUDA detection mechanism. This disables it
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# in cases where it may backfire. One such case is when `cuda` is
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# external and marked with `buildable=false`. `blaspp`'s CMake CUDA
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# detection mechanism finds CUDA but doesn't set certain paths properly
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# which leads to a build issues [1].
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#
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# [1]: https://bitbucket.org/icl/blaspp/issues/6/compile-error-due-to-implicit-cuda
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if '~cuda' in spec:
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args.append('-DCMAKE_CUDA_COMPILER=')
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# Missing:
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#
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# - acml : BLAS_LIBRARY="AMD ACML"
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# BLAS_LIBRARY_THREADING= threaded/sequential
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#
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# - apple : BLAS_LIBRARY="Apple Accelerate" (veclibfort ???)
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#
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if '^mkl' in spec:
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args.append('-DBLAS_LIBRARY="Intel MKL"')
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elif '^essl' in spec:
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args.append('-DBLAS_LIBRARY="IBM ESSL"')
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elif '^openblas' in spec:
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args.append('-DBLAS_LIBRARY="OpenBLAS"')
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elif '^cray-libsci' in spec:
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args.append('-DBLAS_LIBRARY="Cray LibSci"')
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else: # e.g. netlib-lapack
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args.append('-DBLAS_LIBRARY="generic"')
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return args
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