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## page was renamed from Howto/NVIDIA_CUDA
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== NVIDIA CUDA Installation == == Installation ==
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== NVIDIA CUDA Repository ==
Th
is repository contains a given version of CUDA that is parallel installable along with another version.
== NVIDIA official repositories ==
These repositories
contain versions of CUDA that are parallel installables along with another version.

=== CUDA Toolkit ===
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* RHEL/CentOS 7 {{{
yum install http://developer.download.nvidia.com/compute/cuda/repos/rhel7/x86_64/cuda-repo-rhel7-8.0.44-1.x86_64.rpm
yum install cuda
 * RHEL/CentOS 7 {{{
sudo yum install https://developer.download.nvidia.com/compute/cuda/repos/rhel7/x86_64/cuda-repo-rhel7-10.1.105-1.x86_64.rpm
sudo yum install cuda
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* Fedora 23 (and later) {{{
dnf install http://developer.download.nvidia.com/compute/cuda/repos/fedora23/x86_64/cuda-repo-fedora23-8.0.44-1.x86_64.rpm
dnf install cuda
 * RHEL/CentOS 6 {{{
sudo yum install https://developer.download.nvidia.com/compute/cuda/repos/rhel6/x86_64/cuda-repo-rhel6-10.1.105-1.x86_64.rpm
sudo yum install cuda
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== GCC version issue ==
When using a later version of Fedora than what is supported by the NVIDIA CUDA Official repository, you might be unable to compile.
You can either:
* Tweak the /usr/local/cuda-8.0/targets/x86_64-linux/include/host_defines.h to accept the Fedora default compiler.
* Install the appropriate gcc version for CentOS developper toolset. Please see https://www.softwarecollections.org/en/scls/rhscl/devtoolset-4/
{{{
dnf install http://ftp.ciril.fr/pub/linux/centos/7.3.1611/extras/x86_64/Packages/centos-release-scl-2-2.el7.centos.noarch.rpm
dnf install devtoolset-4-toolchain
}}}
You cannot install the whole devtoolset-4 collection, but the toolchain is enough , then each time you need to build using cuda, you start by
{{{
$ scl run devtoolset-4 bash
$ gcc --version
gcc (GCC) 5.2.1 20150902 (Red Hat 5.2.1-2)
Copyright (C) 2015 Free Software Foundation, Inc.
This is free software; see the source for copying conditions. There is NO
warranty; not even for MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE
$ exit
$ gcc --version
gcc --version
gcc (GCC) 6.2.1 20160916 (Red Hat 6.2.1-2)
Copyright © 2016 Free Software Foundation, Inc.
Ce logiciel est libre; voir les sources pour les conditions de copie. Il n'y a PAS
GARANTIE; ni implicite pour le MARCHANDAGE ou pour un BUT PARTICULIER
 * Fedora 29 (and later) {{{
sudo dnf install https://developer.download.nvidia.com/compute/cuda/repos/fedora29/x86_64/cuda-repo-fedora29-10.1.105-1.x86_64.rpm
sudo dnf install cuda
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=== Machine Learning repository ===

Please use the official link: https://developer.nvidia.com/nccl/nccl-download

 * RHEL/CentOS 7 {{{
sudo yum install https://developer.download.nvidia.com/compute/machine-learning/repos/rhel7/x86_64/nvidia-machine-learning-repo-rhel7-1.0.0-1.x86_64.rpm
sudo yum install libcudnn7 libcudnn7-devel libnccl libnccl-devel
}}}

 * Fedora {{{
sudo dnf install https://developer.download.nvidia.com/compute/machine-learning/repos/rhel7/x86_64/nvidia-machine-learning-repo-rhel7-1.0.0-1.x86_64.rpm
sudo dnf install libcudnn7 libcudnn7-devel libnccl libnccl-devel
}}}


=== Legacy NVIDIA 340xx/CUDA 6.5 ===
This repository contains a legacy version of CUDA 6.5 that will works with the NVIDIA 340xx serie

Please use the Official link: https://developer.nvidia.com/cuda-toolkit-65

 * RHEL/CentOS 6 {{{
sudo yum install http://developer.download.nvidia.com/compute/cuda/repos/rhel6/x86_64/cuda-repo-rhel6-6.5-14.x86_64.rpm
sudo yum install cuda
}}}
 * Fedora 20 (and later) {{{
sudo yum install install http://developer.download.nvidia.com/compute/cuda/repos/fedora20/x86_64/cuda-repo-fedora20-6.5-14.x86_64.rpm
sudo yum install cuda
}}}

Please verify to have a compatible compiler.

== Known issues ==
=== GCC version ===
When using a later version of Fedora than what is supported by the NVIDIA CUDA Official repository, you might be unable to compile.
You can either:

 * Tweak the /usr/local/cuda-9.2/targets/x86_64-linux/include/host_defines.h to accept the Fedora default compiler. (Not recommended).

 * Install the appropriate gcc version from developper toolset. It will install in parallel. Please see https://www.softwarecollections.org/en/scls/rhscl/devtoolset-7/

{{{
sudo dnf install http://centos.mirrors.ovh.net/ftp.centos.org/7/extras/x86_64/Packages/centos-release-scl-rh-2-2.el7.centos.noarch.rpm
sudo dnf install http://centos.mirrors.ovh.net/ftp.centos.org/7/updates/x86_64/Packages/libgfortran4-7.2.1-1.2.1.el7_5.x86_64.rpm
sudo dnf install devtoolset-7-toolchain
}}}
You cannot install the whole devtoolset-7 collection, but the toolchain is enough , then each time you need to build using cuda, you start by
{{{
scl run devtoolset-7 bash
gcc --version
gcc (GCC) 7.3.1 20180303 (Red Hat 7.3.1-5)
Copyright (C) 2017 Free Software Foundation, Inc.
This is free software; see the source for copying conditions. There is NO
warranty; not even for MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.
exit
gcc --version
gcc (GCC) 8.1.1 20180712 (Red Hat 8.1.1-5)
Copyright (C) 2018 Free Software Foundation, Inc.
This is free software; see the source for copying conditions. There is NO
warranty; not even for MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.
}}}

=== Which driver Package ===
Both "CUDA" and "RPM Fusion" repositories provide the nvidia driver packages. Usually, the package provided by RPM Fusion is higher. But in case you want to avoid the risk, add this:
{{{
#/etc/yum.repos.d/cuda.repo
[cuda]
name=cuda
...
exclude=akmod-nvidia*,kmod-nvidia*,*nvidia*,nvidia-*,cuda-nvidia-kmod-common,dkms-nvidia,nvidia-libXNVCtrl
}}}


=== NVIDIA provided libOpenCL ===
NVIDIA only advertise OpenCL 1.2 with the binary driver at this time. As a consequence, they provide an old version of libOpenCL.so.1 which works fine with their binary driver.
As most software in Fedora and RPM Fusion are built using a newer libOpenCL, the system linker detects that and issues the following message:
{{{
 /usr/local/cuda-9.2/targets/x86_64-linux/lib/libOpenCL.so.1: no version information available (required by ffmpeg)
}}}

You can either ignore the message or manually delete the libOpenCL.so.1 provided by NVIDIA (run sudo ldconfig once deleted). Please verify to not have other OpenCL providers that might interfere with NVIDIA OpenCL usage.
(looking at /etc/OpenCL/vendors ).

=== Running blender ===
Even when only running blender, you need a CUDA compatible compiler as described above. This is because blender will compile the "CUDA Kernels" optimized for your own GPU. You can run blender with:
{{{
 scl run devtoolset-7 blender
}}}
Once the "CUDA kernels" are compiled, you can run blender normally

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* CUDA Start quide: https://developer.nvidia.com/compute/cuda/8.0/prod/docs/sidebar/CUDA_Quick_Start_Guide-pdf
* CUDA documentation: https://docs.nvidia.com/cuda/index.html
 * CUDA whatsnew : https://developer.nvidia.com/cuda-toolkit/whatsnew

 
* CUDA documentation: https://docs.nvidia.com/cuda/index.html

Installation

This Howto provides a way to install the official NVIDIA packages for CUDA.

NVIDIA official repositories

These repositories contain versions of CUDA that are parallel installables along with another version.

CUDA Toolkit

Please use the Official link: https://developer.nvidia.com/cuda-downloads

  • RHEL/CentOS 7

    sudo yum install https://developer.download.nvidia.com/compute/cuda/repos/rhel7/x86_64/cuda-repo-rhel7-10.1.105-1.x86_64.rpm
    sudo yum install cuda
  • RHEL/CentOS 6

    sudo yum install https://developer.download.nvidia.com/compute/cuda/repos/rhel6/x86_64/cuda-repo-rhel6-10.1.105-1.x86_64.rpm
    sudo yum install cuda
  • Fedora 29 (and later)

    sudo dnf install https://developer.download.nvidia.com/compute/cuda/repos/fedora29/x86_64/cuda-repo-fedora29-10.1.105-1.x86_64.rpm
    sudo dnf install cuda

Machine Learning repository

Please use the official link: https://developer.nvidia.com/nccl/nccl-download

  • RHEL/CentOS 7

    sudo yum install https://developer.download.nvidia.com/compute/machine-learning/repos/rhel7/x86_64/nvidia-machine-learning-repo-rhel7-1.0.0-1.x86_64.rpm
    sudo yum install libcudnn7 libcudnn7-devel libnccl libnccl-devel
  • Fedora

    sudo dnf install https://developer.download.nvidia.com/compute/machine-learning/repos/rhel7/x86_64/nvidia-machine-learning-repo-rhel7-1.0.0-1.x86_64.rpm
    sudo dnf install libcudnn7 libcudnn7-devel libnccl libnccl-devel

Legacy NVIDIA 340xx/CUDA 6.5

This repository contains a legacy version of CUDA 6.5 that will works with the NVIDIA 340xx serie

Please use the Official link: https://developer.nvidia.com/cuda-toolkit-65

  • RHEL/CentOS 6

    sudo yum install http://developer.download.nvidia.com/compute/cuda/repos/rhel6/x86_64/cuda-repo-rhel6-6.5-14.x86_64.rpm
    sudo yum install cuda
  • Fedora 20 (and later)

    sudo yum install install http://developer.download.nvidia.com/compute/cuda/repos/fedora20/x86_64/cuda-repo-fedora20-6.5-14.x86_64.rpm
    sudo yum install cuda

Please verify to have a compatible compiler.

Known issues

GCC version

When using a later version of Fedora than what is supported by the NVIDIA CUDA Official repository, you might be unable to compile. You can either:

sudo dnf install http://centos.mirrors.ovh.net/ftp.centos.org/7/extras/x86_64/Packages/centos-release-scl-rh-2-2.el7.centos.noarch.rpm
sudo dnf install http://centos.mirrors.ovh.net/ftp.centos.org/7/updates/x86_64/Packages/libgfortran4-7.2.1-1.2.1.el7_5.x86_64.rpm
sudo dnf install devtoolset-7-toolchain

You cannot install the whole devtoolset-7 collection, but the toolchain is enough , then each time you need to build using cuda, you start by

scl run devtoolset-7 bash
gcc --version
gcc (GCC) 7.3.1 20180303 (Red Hat 7.3.1-5)
Copyright (C) 2017 Free Software Foundation, Inc.
This is free software; see the source for copying conditions.  There is NO
warranty; not even for MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.
exit
gcc --version
gcc (GCC) 8.1.1 20180712 (Red Hat 8.1.1-5)
Copyright (C) 2018 Free Software Foundation, Inc.
This is free software; see the source for copying conditions.  There is NO
warranty; not even for MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.

Which driver Package

Both "CUDA" and "RPM Fusion" repositories provide the nvidia driver packages. Usually, the package provided by RPM Fusion is higher. But in case you want to avoid the risk, add this:

#/etc/yum.repos.d/cuda.repo
[cuda]
name=cuda
...
exclude=akmod-nvidia*,kmod-nvidia*,*nvidia*,nvidia-*,cuda-nvidia-kmod-common,dkms-nvidia,nvidia-libXNVCtrl

NVIDIA provided libOpenCL

NVIDIA only advertise OpenCL 1.2 with the binary driver at this time. As a consequence, they provide an old version of libOpenCL.so.1 which works fine with their binary driver. As most software in Fedora and RPM Fusion are built using a newer libOpenCL, the system linker detects that and issues the following message:

 /usr/local/cuda-9.2/targets/x86_64-linux/lib/libOpenCL.so.1: no version information available (required by ffmpeg)

You can either ignore the message or manually delete the libOpenCL.so.1 provided by NVIDIA (run sudo ldconfig once deleted). Please verify to not have other OpenCL providers that might interfere with NVIDIA OpenCL usage. (looking at /etc/OpenCL/vendors ).

Running blender

Even when only running blender, you need a CUDA compatible compiler as described above. This is because blender will compile the "CUDA Kernels" optimized for your own GPU. You can run blender with:

 scl run devtoolset-7 blender

Once the "CUDA kernels" are compiled, you can run blender normally

References


CategoryHowto

Howto/CUDA (last edited 2019-04-06 12:42:01 by NicolasChauvet)