/[packages]/cauldron/nvidia-cuda-toolkit/current/SPECS/nvidia-cuda-toolkit.spec
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Contents of /cauldron/nvidia-cuda-toolkit/current/SPECS/nvidia-cuda-toolkit.spec

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Revision 83502 - (show annotations) (download)
Mon Apr 11 21:56:37 2011 UTC (10 years, 5 months ago) by tmb
File size: 4582 byte(s)
rebuild to get repo back in sync
1 %define name nvidia-cuda-toolkit
2 %define version 3.2.16
3 %define release %mkrel 2
4
5 %define driver_ver 260.19.21
6
7 Summary: NVIDIA CUDA Toolkit libraries
8 Name: %{name}
9 Version: %{version}
10 Release: %{release}
11 Source0: cudatoolkit_%{version}_linux_32_ubuntu10.04.run
12 Source1: cudatoolkit_%{version}_linux_64_ubuntu10.04.run
13 Source2: nvidia
14 License: Freeware
15 Group: System/Libraries
16 Url: http://www.nvidia.com/cuda/
17 BuildRoot: %{_tmppath}/%{name}-%{version}-%{release}-buildroot
18 Suggests: nvidia >= %{driver_ver}
19 # We don't require installation of the NVIDIA graphics drivers so that
20 # folks can do CUDA development on systems without NVIDIA hardware.
21
22 %description
23 NVIDIA(R) CUDA(TM) is a general purpose parallel computing architecture
24 that leverages the parallel compute engine in NVIDIA graphics
25 processing units (GPUs) to solve many complex computational problems
26 in a fraction of the time required on a CPU. It includes the CUDA
27 Instruction Set Architecture (ISA) and the parallel compute engine in
28 the GPU. To program to the CUDATM architecture, developers can, today,
29 use C, one of the most widely used high-level programming languages,
30 which can then be run at great performance on a CUDATM enabled
31 processor. Other languages will be supported in the future, including
32 FORTRAN and C++.
33
34 This package contains the libraries and attendant files needed to run
35 programs that make use of CUDA.
36
37 %package devel
38 Summary: NVIDIA CUDA Toolkit development files
39 Group: Development/C
40 Requires: %{name} = %{version}-%{release}
41 Suggests: nvidia-devel >= %{driver_ver}
42 %define _requires_exceptions libcuda.so.3\\|libcudart.so.3
43
44 %description devel
45 NVIDIA(R) CUDA(TM) is a general purpose parallel computing architecture
46 that leverages the parallel compute engine in NVIDIA graphics
47 processing units (GPUs) to solve many complex computational problems
48 in a fraction of the time required on a CPU. It includes the CUDA
49 Instruction Set Architecture (ISA) and the parallel compute engine in
50 the GPU. To program to the CUDATM architecture, developers can, today,
51 use C, one of the most widely used high-level programming languages,
52 which can then be run at great performance on a CUDATM enabled
53 processor. Other languages will be supported in the future, including
54 FORTRAN and C++.
55
56 This package contains the development files needed to build programs
57 that make use of CUDA.
58
59 %package -n nvidia-compute-profiler
60 Summary: NVIDIA Compute Visual Profiler
61 Group: Development/Other
62 Requires: %{name} = %{version}-%{release}
63 Obsoletes: nvidia-cuda-profiler, nvidia-opencl-profiler
64 Suggests: nvidia-devel >= %{driver_ver}
65 Suggests: qt4-assistant
66
67 %description -n nvidia-compute-profiler
68 NVIDIA(R) CUDA(TM) is a general purpose parallel computing architecture
69 that leverages the parallel compute engine in NVIDIA graphics
70 processing units (GPUs) to solve many complex computational problems
71 in a fraction of the time required on a CPU. It includes the CUDA
72 Instruction Set Architecture (ISA) and the parallel compute engine in
73 the GPU. To program to the CUDATM architecture, developers can, today,
74 use C, one of the most widely used high-level programming languages,
75 which can then be run at great performance on a CUDATM enabled
76 processor. Other languages will be supported in the future, including
77 FORTRAN and C++.
78
79 This package contains the Compute Visual Profiler for CUDA and OpenCL.
80
81 %prep
82 %setup -q -T -c %{name}-%{version}
83
84 %install
85 %__rm -rf %{buildroot}
86
87 %__install -d -m 755 %{buildroot}%{_usr}
88
89 %ifarch %ix86
90 bash %SOURCE0 --tar xf -C %{buildroot}%{_usr}
91 %else
92 bash %SOURCE1 --tar xf -C %{buildroot}%{_usr}
93 %__rm -rf %{buildroot}/usr/lib
94 %__sed -i 's/lib/lib64/g' %{buildroot}%{_bindir}/nvcc.profile
95 %endif
96
97 %__mv %{buildroot}%{_usr}/doc ./
98
99 %__rm -rf %{buildroot}%{_usr}/src
100 %__rm -rf %{buildroot}%{_usr}/install-linux.pl
101
102 %__mv %{buildroot}%{_usr}/computeprof/bin/computeprof %{buildroot}%{_bindir}/
103 %__mkdir computeprofdoc
104 %__mv %{buildroot}%{_usr}/computeprof/*.txt computeprofdoc/
105 %__mv %{buildroot}%{_usr}/computeprof/doc/* computeprofdoc/
106 %__mv %{buildroot}%{_usr}/computeprof/projects computeprofdoc/
107 %__rm -rf %{buildroot}%{_usr}/computeprof
108
109 %__install -D -m 755 %SOURCE2 %{buildroot}%{_sysconfdir}/init.d/nvidia
110
111 %clean
112 %__rm -rf %{buildroot}
113
114 %post -p /sbin/ldconfig
115
116 %postun -p /sbin/ldconfig
117
118 %files
119 %_libdir/*.so.*
120 %_sysconfdir/init.d/*
121
122 %files devel
123 %defattr(-,root,root)
124 %doc doc/*
125 %_bindir/*
126 %exclude %_bindir/computeprof
127 %_libdir/*.so
128 %_includedir/*
129 %_usr/open64/*
130
131 %files -n nvidia-compute-profiler
132 %defattr(-,root,root)
133 %doc computeprofdoc/*
134 %_bindir/computeprof
135
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