new package: miniGMG (#4849)

* new package: miniGMG

* changed based on comments

* removed cuda version

1 files changed, 67 insertions, 0 deletions

diff --git a/var/spack/repos/builtin/packages/minigmg/package.py b/var/spack/repos/builtin/packages/minigmg/package.py
new file mode 100644
index 0000000000..799fb1ee6f
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+++ b/var/spack/repos/builtin/packages/minigmg/package.py
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+##############################################################################
+# Copyright (c) 2013-2016, Lawrence Livermore National Security, LLC.
+# Produced at the Lawrence Livermore National Laboratory.
+#
+# This file is part of Spack.
+# Created by Todd Gamblin, tgamblin@llnl.gov, All rights reserved.
+# LLNL-CODE-647188
+#
+# For details, see https://github.com/llnl/spack
+# Please also see the LICENSE file for our notice and the LGPL.
+#
+# This program is free software; you can redistribute it and/or modify
+# it under the terms of the GNU Lesser General Public License (as
+# published by the Free Software Foundation) version 2.1, February 1999.
+#
+# This program is distributed in the hope that it will be useful, but
+# WITHOUT ANY WARRANTY; without even the IMPLIED WARRANTY OF
+# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the terms and
+# conditions of the GNU Lesser General Public License for more details.
+#
+# You should have received a copy of the GNU Lesser General Public
+# License along with this program; if not, write to the Free Software
+# Foundation, Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA
+##############################################################################
+from spack import *
+import glob
+
+
+class Minigmg(Package):
+    """miniGMG is a compact benchmark for understanding the performance
+    challenges associated with geometric multigrid solvers
+    found in applications built from AMR MG frameworks
+    like CHOMBO or BoxLib when running
+    on modern multi- and manycore-based supercomputers.
+    It includes both productive reference examples as well as
+    highly-optimized implementations for CPUs and GPUs.
+    It is sufficiently general that it has been used to evaluate
+    a broad range of research topics including PGAS programming models
+    and algorithmic tradeoffs inherit in multigrid. miniGMG was developed
+    under the CACHE Joint Math-CS Institute.
+
+    Note, miniGMG code has been supersceded by HPGMG. """
+
+    homepage = "http://crd.lbl.gov/departments/computer-science/PAR/research/previous-projects/miniGMG/"
+    url      = "http://crd.lbl.gov/assets/Uploads/FTG/Projects/miniGMG/miniGMG.tar.gz"
+
+    version('master', '975a2a118403fc0024b5e04cef280e95')
+
+    depends_on('mpi')
+
+    phases = ['build', 'install']
+
+    def build(self, spec, prefix):
+        cc = Executable(spec['mpi'].mpicc)
+        cc('-O3', self.compiler.openmp_flag, 'miniGMG.c',
+            'mg.c', 'box.c', 'solver.c', 'operators.ompif.c', 'timer.x86.c',
+            '-D__MPI', '-D__COLLABORATIVE_THREADING=6',
+            '-D__TEST_MG_CONVERGENCE', '-D__PRINT_NORM', '-D__USE_BICGSTAB',
+            '-o', 'run.miniGMG', '-lm')
+
+    def install(self, spec, prefix):
+        mkdir(prefix.bin)
+        install('run.miniGMG', prefix.bin)
+        mkdir(prefix.jobs)
+        files = glob.glob('job*')
+        for f in files:
+            install(f, prefix.jobs)