abigail#abilina:~/Downloads$ sudo dpkg -i cuda-repo-ubuntu1604_8.0.61-1_amd64.deb
Selecting previously unselected package cuda-repo-ubuntu1604.
(Reading database ... 205999 files and directories currently installed.)
Preparing to unpack cuda-repo-ubuntu1604_8.0.61-1_amd64.deb ...
Unpacking cuda-repo-ubuntu1604 (8.0.61-1) ...
Setting up cuda-repo-ubuntu1604 (8.0.61-1) ...
Warning: The postinst maintainerscript of the package cuda-repo-ubuntu1604
Warning: seems to use apt-key (provided by apt) without depending on gnupg or gnupg2.
Warning: This will BREAK in the future and should be fixed by the package maintainer(s).
Note: Check first if apt-key functionality is needed at all - it probably isn't!
Warning: apt-key should not be used in scripts (called from postinst maintainerscript of the package cuda-repo-ubuntu1604)
OK
abigail#abilina:~/Downloads$ sudo apt-get install cuda
Reading package lists... Done
Building dependency tree
Reading state information... Done
Some packages could not be installed. This may mean that you have
requested an impossible situation or if you are using the unstable
distribution that some required packages have not yet been created
or been moved out of Incoming.
The following information may help to resolve the situation:
The following packages have unmet dependencies:
cuda : Depends: cuda-8-0 (>= 8.0.61) but it is not going to be installed
E: Unable to correct problems, you have held broken packages.
My ubuntu version is 17.04. Does this mean my Linux currently can't install CUDA? I want to install TensorFlow with GPU support.
Per suggestion:
abigail#abilina:~/Downloads$ sudo apt-get -f install
Reading package lists... Done
Building dependency tree
Reading state information... Done
0 upgraded, 0 newly installed, 0 to remove and 0 not upgraded.
https://launchpad.net/ubuntu/zesty/amd64/nvidia-cuda-toolkit
above is the correct one.
apt-get install nvidia-cuda-toolkit
but remember the cuda installed through apt were installed in different location. manually create ln -s at /usr/local/cuda for include,lib64,and bin
I have successfully installed CUDA 8.0 + the latest patch from NVIDIA on Ubuntu 17.04:
Download the .run file from https://developer.nvidia.com/cuda-downloads, choosing Ubuntu 16.04 (Base Installer)
You will not be able to install it by just running, because it is looking for a file called InstallUtils.pm which is not present in Ubuntu 17.04, but curiously, is present in the .run file - so: unpack the .run file using ./cuda*.run --tar mxvf
copy InstallUtils.pm (should be in the /bin path) to /usr/lib/x86_64-linux-gnu/perl-base
Run the installer (You may want to say no to the driver install step to keep the one you install through apt - I'm using 381.22, because 375.26, which is provided by the .run file does not support my 1080ti)
gcc 6 is incompatible with CUDA, but this is easily remedied for compiling the sample files: just add export EXTRA_NVCCFLAGS="-Xcompiler -std=c++98" to your bashrc file, and comment out
from one of the headers (I think it was host_config.h, but you'll see it once you try to compile) - comment out these lines:
#if __GNUC__ > 5 || (__GNUC__ == 5 && __GNUC_MINOR__ > 3)
#error -- unsupported GNU version! gcc versions later than 5.3 are not supported!
This is all from memory, so hopefully it's accurate enough.
I managed to find this solution thanks to these useful posts:
https://devtalk.nvidia.com/default/topic/983777/can-t-locate-installutils-pm-in-inc/
https://devtalk.nvidia.com/default/topic/949770/cuda-8-0rc-supporting-gcc6-/
For ubuntu 17.04, I had to use cuda 9.0 (deb version)
https://developer.nvidia.com/cuda-release-candidate-download
I couldn't get it to work otherwise. Cuda 8.0 needs gcc 5.3.1 but cuda 9.0 is compatible with gcc 6.3.0 which is installed on ubuntu 17.04 automatically.
More precisely, this is what I did:
On Ubuntu 17.04, install CUDA 9.0 — you can currently download the beta version
https://developer.nvidia.com/cuda-release-candidate-download
I downloaded the .deb file and haven’t had any problems — follow the steps they recommend when you download cuda 9.0
sudo dpkg -i cuda-repo-ubuntu1704-9-0-local-rc_9.0.103-1_amd64.deb
sudo apt-key add /var/cuda-repo-9.0-local-rc/7fa2af80.pub
sudo apt-get update
sudo apt-get install cuda
Then follow the post installation steps from the nvidia instructions (i.e., setting PATH and LD_LIBRARY_PATH)
http://docs.nvidia.com/cuda/cuda-installation-guide-linux/index.html#post-installation-actions)
export PATH=/usr/local/cuda-9.0/bin${PATH:+:${PATH}}
export LD_LIBRARY_PATH=/usr/local/cuda-9.0/lib64 ${LD_LIBRARY_PATH:+:${LD_LIBRARY_PATH}}
Cuda 9 is compatible with gcc 6.3.0 (which comes with 17.04). I used arch=sm_52 and sometimes for my make files have to go ‘make clean’.
Installing Cuda 9.0 was the simplest solution in my case.
Alternatively, if you'd prefer cuda 8, you can download the deb file and then use the command
dpkg-deb -x cuda_8.*.deb /usr/local/cuda-8.0
to extract the contents from the deb file and have them placed in the desired directory.
Source: http://docs.nvidia.com/cuda/cuda-installation-guide-linux/index.html#advanced-setup)
Related
I need to test if some firmware is compatible with older ethtool versions.
The machine I am using currently have ethtool version 5.16, but I need to install ethtool version 5.13
I got the compressed file from https://mirrors.edge.kernel.org/pub/software/network/ethtool/ and have used tar -zxvf https... to extract the files. This extracts a directory with the contents shown below:
After reading the INSTALL file, I ran ./configure but it gave me the following error: configure: error: The pkg-config script could not be found or is too old. Make sure it is in your PATH or set the PKG_CONFIG environment variable to the full path to pkg-config
This meant that I could not run make or make install and thus am stuck.
After speaking to colleagues, the solution was found:
apt-get install -y pkg-config. Thereafter the following package was also needed: apt-get install -y libmnl-dev
Simple installed it with ./configure, make and make install and saw the ethtool version was as desired.
I am trying to install Pipewire in my Ubuntu 16.04 x86 amd64 machine using instructions found here : https://pipewire.org/#getting
./autogen.sh --prefix=$PREFIX
On running the above command, I get this error
spa/meson.build:29:4: ERROR: Dependency "bluez" not found, tried pkgconfig and cmake
I have installed bluez already. This is the output for running
**sudo apt-get install bluez**
Reading package lists... Done
Building dependency tree
Reading state information... Done
bluez is already the newest version (5.37-0ubuntu5.3).
0 upgraded, 0 newly installed, 0 to remove and 19 not upgraded.
The files that are required to do development on top of a package are often separate (since this is really only needed by developers, and would take up too much size for no reason otherwise).
In your case, the package you're looking for is libbluetooth-dev. So you can do sudo apt install libbluetooth-dev
I want to install janus-gateway on CentOS7.
I read the following document and tried installation.
https://github.com/meetecho/janus-gateway/blob/master/README.md
git clone https://github.com/meetecho/janus-gateway.git
cd janus-gateway
sh autogen.sh
./configure --prefix=/opt/janus
However, configuring janus-gateway will cause an error. The error is as follows.
checking if libtool supports shared libraries... yes
checking whether to build shared libraries... yes
checking whether to build static libraries... no
checking for pkg-config... /bin/pkg-config
checking pkg-config is at least version 0.9.0... yes
checking for JANUS... no
configure: error: Package requirements (
glib-2.0 >= 2.34
libconfig
nice
jansson >= 2.5
libssl >= 1.0.1
libcrypto
) were not met:
No package 'nice' found
Consider adjusting the PKG_CONFIG_PATH environment variable if you
installed software in a non-standard prefix.
Alternatively, you may set the environment variables JANUS_CFLAGS
and JANUS_LIBS to avoid the need to call pkg-config.
See the pkg-config man page for more details.
I installed libnice(libnice-0.1.3-4.el7.x86_64) in the following way.
yum install libnice
How can I solve it?
Thank you.
try this and rebuild
echo "export PKG_CONFIG_PATH=/usr/lib/pkgconfig" >> ~/.bashrc
source ~/.bashrc
Disclaimer: I am using Ubuntu 18.04 when testing this.
If you are using Ubuntu system and trying to install Janus and running this code
./configure --prefix=/opt/janus
And then getting this error: No package 'nice' found
Make sure you have been installation of the nice from aptitude.
sudo install aptitude
aptitude install libmicrohttpd-dev libjansson-dev \
libssl-dev libsrtp-dev libsofia-sip-ua-dev libglib2.0-dev \
libopus-dev libogg-dev libcurl4-openssl-dev liblua5.3-dev \
libconfig-dev pkg-config gengetopt libtool automake
For some reason installation of nice using the answer from Frank, Ahmet or Zallfire doesn't work in Ubuntu. It has to be installed using aptitude.
You should download libnice source code to install.
https://gitlab.freedesktop.org/libnice/libnice
You need the development libnice.
yum install libnice-devel
I am trying to run a bit of python code that uses tensorflow-gpu. However, when the process tries to run, I'm getting the following error:
2018-04-13 20:03:49.215876: E tensorflow/stream_executor/cuda/cuda_dnn.cc:396] Loaded runtime CuDNN library: 7102 (compatibility version 7100) but source was compiled with 7005 (compatibility version 7000). If using a binary install, upgrade your CuDNN library to match. If building from sources, make sure the library loaded at runtime matches a compatible version specified during compile configuration.
2018-04-13 20:03:49.220783: F tensorflow/core/kernels/conv_ops.cc:712] Check failed: stream->parent()->GetConvolveAlgorithms( conv_parameters.ShouldIncludeWinogradNonfusedAlgo(), &algorithms)
However, I typed env and it listed CUDNN_VERSION=7.0.5.15 and LD_LIBRARY_PATH=/usr/local/cuda/extras/CUPTI/lib64:/usr/local/nvidia/lib:/usr/local/nvidia/lib64
I installed cudnn 7.0.5 by downloading and copying the relevant files into /user/local/cuda/
Why is this error occurring? I am using a kubernetes backed cluster
I fixed it using this post from askubuntu
Pasting the instructions from that post here:
Step 0: Install cuda from the standard repositories. (See How can I install CUDA on Ubuntu 16.04?)
Step 1: Register an nvidia developer account and download cudnn here (about 80 MB)
Step 2: Check where your cuda installation is. For the installation from the repository it is /usr/lib/... and /usr/include. Otherwise, it will be /usr/local/cuda/ or /usr/local/cuda-<version>. You can check it with which nvcc or ldconfig -p | grep cuda
Step 3: Copy the files:
$ cd folder/extracted/contents
$ sudo cp -P include/cudnn.h /usr/include
$ sudo cp -P lib64/libcudnn* /usr/lib/x86_64-linux-gnu/
$ sudo chmod a+r /usr/lib/x86_64-linux-gnu/libcudnn*
Basically, on the cudnn installation instruction, it only tells you to copy your cudnn.h and libcudnn* files to the cuda folder. However, in addition to that, one also needs to copy those files inside the systems main include and lib64 folders. That will fix this problem.
Related Question 1
Related Question 2
[Error Log]
C:\Users\Hima\Documents\Installers\python\packages>python -m pip install lxml-3.4.4-cp34-none-win_amd64.whl
lxml-3.4.4-cp34-none-win_amd64.whl is not a supported wheel on this platform.
[Environment]
Windows x86 (64-bit)
Installed Visual Studio C++ 2014
Python 3.4
I use pip (or pip3.4.exe; built-in to Python 3.4) to pip install lxml
[Issues]
1. The lxml file from http://www.lfd.uci.edu/~gohlke/pythonlibs/#lxml shows as not supported.
2. In the following Package Index for lxml, there isn't a suitable lxml file for 64 bit and Python 3.4.
https://pypi.python.org/pypi/lxml/3.4.4
I have been struggling with this today. I found, elsewhere on stackoverflow.com, this two-part and quick solution, which resulted in python no longer complaining when I tried to use lxml:
Go to this repository and download a version which matches your Python installation (the version number, and 32- vs 64-bit. I use Python 3.5.1 64-bit, installed on Windows 10, so on that page, I chose lxml-3.6.0-cp35-cp35m-win_amd64.whl.
You say you use Python 3.4, so use a version that matches that (or maybe the one you already have).
There is some helpful information at the top of the page about which version of CPython the files are built against.
The output of python -v will also tell you which version of MSVC++ was used to build your version of the python executable.
This answer is useful for determining MSVC versions from the output of python -v (which contains a build number instead of a version number).
My download directory is d:\Downloads. Python must be in your PATH environment variable for the next step to work. Use a command like the following, changing "D:\Downloads" to the pathname to your download directory. Then, at a DOS prompt, type:
python -m pip install "D:\Downloads\lxml-3.6.0-cp35-cp35m-win_amd64.whl" lxml-3.6.0-cp35-cp35m-win_amd64.whl
My config:
Python 3.5
Windows 10
Downloaded lxml-3.6.0-cp35-cp35m-win_amd64.whl from http://www.lfd.uci.edu/~gohlke/pythonlibs/#lxml
Copy this file to: c:\Program Files\Python35\
first in cmd line:
c:\Program Files\Python35>py -m pip install --upgrade pip
Then in cmd line:
c:\Program Files\Python35>py -m pip install lxml-3.6.0-cp35-cp35m-win_amd64.whl
And it's done