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authorKen Raffenetti <raffenet@users.noreply.github.com>2022-04-20 02:56:02 -0500
committerGitHub <noreply@github.com>2022-04-20 09:56:02 +0200
commita43a633b2ad3a8dd79c24ab059104020b840d41f (patch)
tree37f8079911a57f2a55fe910e211e6ede717e9df8 /var
parent5e00dffe7f519d61fa474d183d2623fbce0eae91 (diff)
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yaksa: add new package (#29877)
Diffstat (limited to 'var')
-rw-r--r--var/spack/repos/builtin/packages/yaksa/package.py45
1 files changed, 45 insertions, 0 deletions
diff --git a/var/spack/repos/builtin/packages/yaksa/package.py b/var/spack/repos/builtin/packages/yaksa/package.py
new file mode 100644
index 0000000000..30dc80da16
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+++ b/var/spack/repos/builtin/packages/yaksa/package.py
@@ -0,0 +1,45 @@
+# Copyright 2013-2022 Lawrence Livermore National Security, LLC and other
+# Spack Project Developers. See the top-level COPYRIGHT file for details.
+#
+# SPDX-License-Identifier: (Apache-2.0 OR MIT)
+
+from spack import *
+
+
+class Yaksa(AutotoolsPackage, CudaPackage):
+ """Yaksa is a high-performance datatype engine for expressing,
+ managing and manipulating data present in noncontiguous memory
+ regions. It provides portable abstractions for structured
+ noncontiguous data layouts that are much more comprehensive compared
+ with traditional I/O vectors.
+
+ Yaksa imitates parts of the MPI Datatype system, but adds additional
+ functionality that would allow it to be used independent of MPI. It
+ provides routines for packing/unpacking, creating I/O vectors (array
+ of contiguous segments) and flattening/unflattening datatypes into
+ process-portable formats.
+
+ Yaksa's backend includes support for CPUs as well as different
+ GPUs."""
+
+ homepage = "https://www.yaksa.org"
+ url = "https://github.com/pmodels/yaksa/archive/refs/tags/v0.2.tar.gz"
+ maintainers = ['raffenet', 'yfguo', 'hzhou']
+
+ version('0.2', sha256='9401cb6153dc8c34ddb9781bbabd418fd26b0a27b5da3294ecc21af7be9c86f2')
+
+ depends_on('autoconf', type='build')
+ depends_on('automake', type='build')
+ depends_on('libtool', type='build')
+ depends_on('m4', type='build')
+ depends_on('python@3:', type='build')
+
+ def autoreconf(self, spec, prefix):
+ sh = which('sh')
+ sh('autogen.sh')
+
+ def configure_args(self):
+ config_args = []
+ config_args += self.with_or_without('cuda', activation_value='prefix')
+
+ return config_args