%global _empty_manifest_terminate_build 0
Name:		python-kerncraft
Version:	0.8.15
Release:	1
Summary:	Loop Kernel Analysis and Performance Modeling Toolkit
License:	AGPLv3
URL:		https://github.com/RRZE-HPC/kerncraft
Source0:	https://mirrors.nju.edu.cn/pypi/web/packages/aa/f8/0c143d59370bf6c2f3d8d078a30d5da3c1b49394f1f02f37f88f3aae8324/kerncraft-0.8.15.tar.gz
BuildArch:	noarch


%description
Loop Kernel Analysis and Performance Modeling Toolkit
This tool allows automatic analysis of loop kernels using the Execution Cache Memory (ECM) model,
the Roofline model and actual benchmarks. kerncraft provides a framework to investigate the
data reuse and cache requirements by static code analysis. In combination with the Intel IACA tool
kerncraft can give a good overview of both in-core and memory bottlenecks and use that data to
apply performance models.
For a detailed documentation see publications in `<doc/>`_.

%package -n python3-kerncraft
Summary:	Loop Kernel Analysis and Performance Modeling Toolkit
Provides:	python-kerncraft
BuildRequires:	python3-devel
BuildRequires:	python3-setuptools
BuildRequires:	python3-pip
%description -n python3-kerncraft
Loop Kernel Analysis and Performance Modeling Toolkit
This tool allows automatic analysis of loop kernels using the Execution Cache Memory (ECM) model,
the Roofline model and actual benchmarks. kerncraft provides a framework to investigate the
data reuse and cache requirements by static code analysis. In combination with the Intel IACA tool
kerncraft can give a good overview of both in-core and memory bottlenecks and use that data to
apply performance models.
For a detailed documentation see publications in `<doc/>`_.

%package help
Summary:	Development documents and examples for kerncraft
Provides:	python3-kerncraft-doc
%description help
Loop Kernel Analysis and Performance Modeling Toolkit
This tool allows automatic analysis of loop kernels using the Execution Cache Memory (ECM) model,
the Roofline model and actual benchmarks. kerncraft provides a framework to investigate the
data reuse and cache requirements by static code analysis. In combination with the Intel IACA tool
kerncraft can give a good overview of both in-core and memory bottlenecks and use that data to
apply performance models.
For a detailed documentation see publications in `<doc/>`_.

%prep
%autosetup -n kerncraft-0.8.15

%build
%py3_build

%install
%py3_install
install -d -m755 %{buildroot}/%{_pkgdocdir}
if [ -d doc ]; then cp -arf doc %{buildroot}/%{_pkgdocdir}; fi
if [ -d docs ]; then cp -arf docs %{buildroot}/%{_pkgdocdir}; fi
if [ -d example ]; then cp -arf example %{buildroot}/%{_pkgdocdir}; fi
if [ -d examples ]; then cp -arf examples %{buildroot}/%{_pkgdocdir}; fi
pushd %{buildroot}
if [ -d usr/lib ]; then
	find usr/lib -type f -printf "/%h/%f\n" >> filelist.lst
fi
if [ -d usr/lib64 ]; then
	find usr/lib64 -type f -printf "/%h/%f\n" >> filelist.lst
fi
if [ -d usr/bin ]; then
	find usr/bin -type f -printf "/%h/%f\n" >> filelist.lst
fi
if [ -d usr/sbin ]; then
	find usr/sbin -type f -printf "/%h/%f\n" >> filelist.lst
fi
touch doclist.lst
if [ -d usr/share/man ]; then
	find usr/share/man -type f -printf "/%h/%f.gz\n" >> doclist.lst
fi
popd
mv %{buildroot}/filelist.lst .
mv %{buildroot}/doclist.lst .

%files -n python3-kerncraft -f filelist.lst
%dir %{python3_sitelib}/*

%files help -f doclist.lst
%{_docdir}/*

%changelog
* Tue May 30 2023 Python_Bot <Python_Bot@openeuler.org> - 0.8.15-1
- Package Spec generated