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This page details the build of our [[DIGITS DevBox]]. There's also a page giving information on [[Using the DevBox]]. nVIDIA, famous for their incredibly poor supply-chain and inventory management, have been saying [https://developer.nvidia.com/devbo "Please note that we are sold out of our inventory of the DIGITS DevBox, and no new systems are being built"] since shortly after the [https://en.wikipedia.org/wiki/GeForce_10_series Titax X] was the latest and greatest thing (i.e., somewhere around 2016). But it's pretty straight forward to update [https://www.azken.com/download/DIGITS_DEVBOX_DESIGN_GUIDE.pdf their spec].
==Introduction==
===Specification===
<onlyinclude>[[File:Top1000.jpg|right|300px]] Our [[DIGITS DevBox]], affectionately named "Bastard"after Lois McMaster Bujold's fifth God, has a XEON e5-2620v3 processor, 256GB of DDR4 RAM, two GPUs - one Titan RTX and one Titan Xp - with room for two more, a 500GB SSD hard drive (mounting /), and an 8TB RAID5 array bcached with a 512GB m.2 drive (mounting the /bulk share, which is available over samba). It runs Ubuntu 18.04, CUDA 10.1 (and CUDA 10 under conda)0, cuDNN 7.56.1, Anaconda3-2019.03, python 3.7, tensorflow 1.13, digits 6, and other useful machine learning tools/libraries.</onlyinclude>
===Documentation===
The DevBox is currently unavailable from Amazon [https://www.amazon.com/Lambda-Deep-Learning-DevBox-Preinstalled/dp/B01BCDK1KC], and at around $15k buying one is prohibitive for most people. Some firms, including Lamdba Labs [https://lambdalabs.com/deep-learning/workstations/4-gpu], Bizon-tech [https://bizon-tech.com/us/bizon-g3000], are selling variants on them, but their prices are high too and the details on their specs are limited (the MoBo and config details are missing entirely).
But the parts ' cost is perhaps $4-5k now for a massive update to the original spec! So this page goes through everything required to put one together and get it up and running.
==Hardware==
Notes:
*We will do RAID 5 array in software, rather using X99 through the BIOS
 
What's really crucial is that all the hardware is visible and that we are NOT using UEFI. With UEFI, there is an issue with the drivers not being properly signed under secure boot.
==Software==
Give the box a reboot!
 
===X Windows===
 
If you install the video driver before installing Xwindows, you will need to manually edit the Xwindows config files. So, now install the X window system. The easiest way is:
tasksel
And choose your favorite. We used Ubuntu Desktop.
 
And reboot again to make sure that everything is working nicely.
===Video Drivers===
====Hardware check====The first build of this box was done with an installation of CUDA 10.1, which automatically installed version 418.67 of the NVIDIA driver. We then installed CUDA 10.0 under conda to support Tensorflow 1.13. All went mostly well, and the history of this page contains the instructions. However, at some point, likely because of an OS update, the video driver(s) stopped working. This page now describes the second build (as if it were a build from scratch). [[Addressing Ubuntu NVIDIA Issues]] provides additional information.
Check that the hardware is being seen: lspci -vk 05:00.0 VGA compatible controller: NVIDIA Corporation GP102 [TITAN Xp] (rev a1) (prog-if 00 [VGA controller]) Subsystem: NVIDIA Corporation GP102 [TITAN Xp] Flags: bus master, fast devsel, latency 0, IRQ 78, NUMA node 0 Memory at fa000000 (32-bit, non-prefetchable) [size=16M] Memory at c0000000 (64-bit, prefetchable) [size=256M] Memory at d0000000 (64-bit, prefetchable) [size=32M] I/O ports at d000 [sizeHardware and Drivers=128] Expansion ROM at 000c0000 [disabled] [size=128K] Capabilities: [60] Power Management version 3 Capabilities: [68] MSI: Enable+ Count=1/1 Maskable- 64bit+ Capabilities: [78] Express Legacy Endpoint, MSI 00 Capabilities: [100] Virtual Channel Capabilities: [250] Latency Tolerance Reporting Capabilities: [128] Power Budgeting <?> Capabilities: [420] Advanced Error Reporting Capabilities: [600] Vendor Specific Information: ID=0001 Rev=1 Len=024 Capabilities: [900] #19 Kernel driver in use: nouveau Kernel modules: nvidiafb, nouveau 06:00.0 VGA compatible controller: NVIDIA Corporation Device 1e02 (rev a1) (prog -if 00 [VGA controller]) Subsystem: NVIDIA Corporation Device 12a3 Flags: fast devsel, IRQ 24, NUMA node 0 Memory at f8000000 (32-bit, non-prefetchable) [size=16M] Memory at a0000000 (64-bit, prefetchable) [size=256M] Memory at b0000000 (64-bit, prefetchable) [size=32M] I/O ports at c000 [size=128] Expansion ROM at f9000000 [disabled] [size=512K] Capabilities: [60] Power Management version 3 Capabilities: [68] MSI: Enable- Count=1/1 Maskable- 64bit+ Capabilities: [78] Express Legacy Endpoint, MSI 00 Capabilities: [100] Virtual Channel Capabilities: [250] Latency Tolerance Reporting Capabilities: [258] L1 PM Substates Capabilities: [128] Power Budgeting <?> Capabilities: [420] Advanced Error Reporting Capabilities: [600] Vendor Specific Information: ID=0001 Rev=1 Len=024 Capabilities: [900] #19 Capabilities: [bb0] #15 Kernel modules: nvidiafb, nouveau
This looks good. The second card Check the hardware is the Titan RTX (see httpsbeing seen and what driver is being used with://devicehunt.com/view/type/pci/vendor/10DE/device/1E02). lspci -vk
Currently we are using the nouveau driver for the Xp, and have no driver loaded for the RTX.
driver : xserver-xorg-video-nouveau - distro free builtin
You could install the driver directly now using, say, apt install nvidia-430. But don't! ====CUDA==== Get CUDA 10.1 and have it install its preferred driver (418.67): *The installation instructions are here: https://docs.nvidia.com/cuda/cuda-installation-guide-linux/index.html*You can down load CUDA from here: https://developer.nvidia.com/cuda-downloads?target_os=Linux&target_arch=x86_64&target_distro=Ubuntu&target_version=1804&target_type=runfilelocal Essentially, first install build-essential, which gets you gcc. Then blacklist the nouveau driver (see https://docs.nvidia.com/cuda/cuda-installation-guide-linux/index.html#runfile-nouveau) and reboot (to a text terminal, if you have deviated from these instructions and already installed X Windows) so that it isn't loaded.
apt-get install build-essential
gcc --version
wget https://developer.nvidia.com/compute/cuda/10.1/Prod/local_installers/cuda_10.1.168_418.67_linux.run
vi /etc/modprobe.d/blacklist-nouveau.conf
blacklist nouveau
update-initramfs -u
shutdown -r now
Reboot to a text terminal
lspci -vk
Shows no kernel driver in use!
Install the driver!  apt install nvidia-driver-430 ====CUDA==== Get CUDA 10.0, rather than 10.1. Although 10.1 is the latest version at the time of writing, it won't work with Tensorflow 1.13, so you'll just end up installing 10.0 under conda anyway. *The installation instructions are here: https://docs.nvidia.com/cuda/cuda-installation-guide-linux/index.html*You can down load CUDA 10.0 from here: https://developer.nvidia.com/cuda-10.0-download-archive?target_os=Linux&target_arch=x86_64&target_distro=Ubuntu&target_version=1804&target_type=runfilelocalEssentially, first install build-essential, which gets you gcc.  Then run the installer script.and DO NOT install the driver (don't worry about the warning, it will work fine!): sh cuda_10.10.168_418130_410.67_linux48_linux.run  Do you accept the previously read EULA? accept/decline/quit: accept Install NVIDIA Accelerated Graphics Driver for Linux-x86_64 410.48? (y)es/(n)o/(q)uit: n
=========== Install the CUDA 10.0 Toolkit? = Summary = =========== (y)es/(n)o/(q)uit: y
Driver: Installed Enter Toolkit Location Toolkit: Installed in [ default is /usr/local/cuda-10.1/ Samples0 ]: Installed in /home/ed/, but missing recommended libraries
Please make sure that - PATH includes Do you want to install a symbolic link at /usr/local/cuda-10.1/bin? - LD_LIBRARY_PATH includes /usr/local/cuda-10.1/lib64, or, add /usr/local/cuda-10.1/lib64 to (y)es/etc(n)o/ld.so.conf and run ldconfig as root(q)uit: y
To uninstall Install the CUDA Toolkit, run cuda-uninstaller in /usr/local/cuda-10.10 Samples? (y)es/bin To uninstall the NVIDIA Driver, run nvidia-uninstall(n)o/(q)uit: y
Enter CUDA Samples Location [ default is /home/ed ]: Installing the CUDA Toolkit in /usr/local/cuda-10.0 ... Missing recommended library: libGLU.so Missing recommended library: libX11.so Missing recommended library: libXi.so Missing recommended library: libXmu.so Missing recommended library: libGL.so Installing the CUDA Samples in /home/ed ... Copying samples to /home/ed/NVIDIA_CUDA-10.0_Samples now... Finished copying samples. =========== = Summary = =========== Driver: Not Selected Toolkit: Installed in /usr/local/cuda-10.0 Samples: Installed in /home/ed, but missing recommended libraries Please make sure that - PATH includes /usr/local/cuda-10.0/bin - LD_LIBRARY_PATH includes /usr/local/cuda-10.0/lib64, or, add /usr/local/cuda-10.0/lib64 to /etc/ld.so.conf and run ldconfig as root To uninstall the CUDA Toolkit, run the uninstall script in /usr/local/cuda-10.0/bin Please see CUDA_Installation_Guide_Linux.pdf in /usr/local/cuda-10.10/doc/pdf for detailed information on setting up CUDA. ***WARNING: Incomplete installation! This installation did not install the CUDA Driver. A driver of version at least 384.00 is required for CUDA 10.0 functionality to work. To install the driver using this installer, run the following command, replacing <CudaInstaller> with the name of this run file: sudo <CudaInstaller>.run -silent -driver Logfile is /vartmp/log/cuda-installercuda_install_2807.log
Fix Now fix the paths. To do this for a single user do: export PATH=/usr/local/cuda-10.10/bin:/usr/local/cuda-10.1/NsightCompute-2019.10${PATH:+:${PATH}} export LD_LIBRARY_PATH=/usr/local/cuda-10.10/lib64${LD_LIBRARY_PATH:+:${LD_LIBRARY_PATH}}
Start But it is better to fix it for everyone by editing your environment file: vi /etc/environment PATH="/usr/local/cuda-10.0/bin:/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin:/usr/games:/usr/local/games" LD_LIBRARY_PATH="/usr/local/cuda-10.0/lib64" With version cuda 10.0, you don't need to edit rc.local to start the persistence daemon:
/usr/bin/nvidia-persistenced --verbose
This should be run at bootInstead, so: vi /etc/rc.local #!/bin/sh -e /usr/bin/nvidia-persistenced --verbose exit 0 chmod +x /etc/rcruns as a service.local Verify the driver: cat /proc/driver/nvidia/version
====Test the installation====
Make the samples in:... cd /usr/local/cuda-10.10/samples
make
And change into the sample directory and run the tests:
Change into the sample directory and run the tests: cd /usr/local/cuda-10.10/samples/bin/x86_64/linux/release
./deviceQuery
./bandwidthTest
And yes, it's a thing of beautyEverything should be good at this point===X Windows=== Now install the X window system. The easiest way is: tasksel And choose your favorite. We used Ubuntu Desktop. And reboot again to make sure that everything is working nicely.
===Bcache===
This section follows https://developer.nvidia.com/rdp/digits-download. Install Docker CE first, following https://docs.docker.com/install/linux/docker-ce/ubuntu/
Then follow https://github.com/NVIDIA/nvidia-docker#quick-start to install docker2, but change the last command to use cuda 10.10
...
sudo apt-get install -y nvidia-docker2
sudo pkill -SIGHUP dockerd
# Test nvidia-smi with the latest official CUDA image
docker run --runtime=nvidia --rm nvidia/cuda:10.10-base nvidia-smi
Then pull DIGITS using docker (https://hub.docker.com/r/nvidia/digits/):
*https://developer.nvidia.com/digits
Note: you can kill docker containers with
docker system prune
====cuDNN====
First, make an installs directory in bulk and copy the installation files over from the RDP (E:\installs\DIGITS DevBox). Then:
cd /bulk/install/
dpkg -i libcudnn7_7.56.1.1034-1+cuda10.1_amd640_amd64.deb dpkg -i libcudnn7-dev_7.56.1.1034-1+cuda10.1_amd640_amd64.deb dpkg -i libcudnn7-doc_7.56.1.1034-1+cuda10.1_amd640_amd64.deb
And test it:
pip install --upgrade tensorflow-gpu
python -c "import tensorflow as tf; tf.enable_eager_execution(); print(tf.reduce_sum(tf.random_normal([1000, 1000])))"
 
And this doesn't work. It turns out that tensorflow 1.13.1 doesn't work with CUDA 10.1! But there is a work around, which is to install cuda10 in conda only (see https://github.com/tensorflow/tensorflow/issues/26182). We are also going to leave the installation of CUDA 10.1 because tensorflow will catch up at some point.
 
Still as researcher (and in the venv):
conda install cudatoolkit
conda install cudnn
conda install tensorflow-gpu
export LD_LIBRARY_PATH=/home/researcher/anaconda3/lib/${LD_LIBRARY_PATH:+:${LD_LIBRARY_PATH}}
python -c "import tensorflow as tf; tf.enable_eager_execution(); print(tf.reduce_sum(tf.random_normal([1000, 1000])))"
AND IT WORKS!
Note: to deactivate the virtual environment:
deactivate
 
Note that adding the anaconda path to /etc/environment makes the virtual environment redundant.
=====PyTorch and SciKit=====
*http://deeplearning.net/software/theano/install_ubuntu.html
==Video Driver Issue=VNC=== In order to use the graphical interface for Matlab and other applications, we need a VNC server.  First, install the VNC client remotely. We use the standalone exe from TigerVNC.  Now install TightVNC, following the instructions: https://www.digitalocean.com/community/tutorials/how-to-install-and-configure-vnc-on-ubuntu-18-04  cd /root apt-get install xfce4 xfce4-goodies As user sudo apt-get install tightvncserver vncserver set password for user (ailia) vncserver -kill :1 mv ~/.vnc/xstartup ~/.vnc/xstartup.bak vi ~/.vnc/xstartup #!/bin/bash xrdb $HOME/.Xresources startxfce4 & vncserver sudo vi /etc/systemd/system/vncserver@.service [Unit] Description=Start TightVNC server at startup After=syslog.target network.target [Service] Type=forking User=uname Group=uname WorkingDirectory=/home/uname PIDFile=/home/ed/.vnc/%H:%i.pid ExecStartPre=-/usr/bin/vncserver -kill :%i > /dev/null 2>&1 ExecStart=/usr/bin/vncserver -depth 24 -geometry 1280x800 :%i ExecStop=/usr/bin/vncserver -kill :%i [Install] WantedBy=multi-user.target Note that changing the color depth breaks it! To make changes (or after the edit) sudo systemctl daemon-reload sudo systemctl enable vncserver@2.service vncserver -kill :2 sudo systemctl start vncserver@2 sudo systemctl status vncserver@2 Stop the server with sudo systemctl stop vncserver@2 Note that we are using :2 because :1 is running our regular Xwindows GUI. Instrucions on how to set up an IP tunnel using PuTTY: https://helpdeskgeek.com/how-to/tunnel-vnc-over-ssh/ ====Connection Issues====
After logging into Coming back to this, I had issues connecting. I set up the tunnel using the saved profile in puTTY.exe and checked to see which local port was listening (it was 5901) and not firewalled using the box sometime laterlistening ports tab under network on resmon.exe (it said allowed, not restricted under firewall status). VNC seemed to be running fine on Bastard, it seems and I tried connecting to localhost::1 (that is 5901 on the video drivers are no longer loadinglocalhost, presumably as a consequence of some update or somethingthrough the tunnel to 5902 on Bastard) using VNC Connect by RealVNC. The connection was refused.
I checked it was listening and there was no firewall: nvidianetstat -settings --query FlatpanelNativeResolutiontlpn tcp 0 0 0.0.0.0:5902 0.0.0.0:* LISTEN 2025/Xtightvnc ufw status ERRORStatus: NVIDIA driver is not loadedinactive
The localhost port seems to be open and listening just fine: cd Test-NetConnection 127.0.0.1 -p 5901 So, presumably, there must be something wrong with the tunnel itself. '''Ignoring the SSH tunnel worked fine: Connect to 192.168.2.202::5902 using the TightVNC (or RealVNC, etc.) client.''' ====Later Notes==== =====Change the resolution===== I came back and changed the resolution to make it work on one of my portrait desktop monitors.See https://www.tightvnc.com/vncserver.1.php As root: vi /etc/systemd/system/vncserver@.service Change line: ExecStart=/usr/localbin/vncserver -depth 24 -geometry 1440x2560 :%i (Note that the size is 2160x3840 divide by 150%). Leave the color depth as it says elsewhere that changes are bad. systemctl daemon-reload systemctl enable vncserver@2.service As Ed: vncserver -kill :2 sudo systemctl start vncserver@2 sudo systemctl status vncserver@2 Exit full screen with ctrl-alt-shift-f. =====Cut And Paste===== Also, try to fix the cut-and-paste issue. See, for example, https://unix.stackexchange.com/questions/35030/how-can-i-copy-paste-data-to-and-from-the-windows-clipboard-to-an-opensuse-clipb As root: apt-get install autocutsel vi ~/.vnc/xstartup #!/bin/bash xrdb $HOME/.Xresources autocutsel -fork startxfce4 & Though this might have been working fine anyway. Just change the terminal and all will be well. =====Use XFCE terminal===== Change Settings: Preferred Applications -> Utilities -> Terminal to XFCE Note that this seems to fix everything but the instructions for customizing the menu are here: https://wiki.xfce.org/howto/customize-menu cat /etc/xdg/menus/xfce-applications.menu ===RDP=== I also installed xrdp: apt install xrdp adduser xrdp ssl-cert #Check the status and that it is listening on 3389 systemctl status xrd netstat -tln #It is listening... vi /etc/xrdp/xrdp.ini #See https://linux.die.net/man/5/xrdp.ini systemctl restart xrdp This gave a dead session (a flat light blue screen with nothing on it), which finally yielded a connection log which said "login successful for display 10, start connecting, connection problems, giving up, some problem." cat /var/log/xrdp-sesman.log There could be some conflict between VNC and RDP. systemctl status xrdp shows "xrdp_wm_log_msg: connection problem, giving up". I tried without success: gsettings set org.gnome.Vino require-encryption false https://askubuntu.com/questions/797973/cudaerror-problem-connecting-windows-10-rdp-into-xrdp vi /etc/X11/Xwrapper.config allowed_users = anybody This was promising as it was previously set to consol.1 https://www.linuxquestions.org/questions/linux-software-2/xrdp-under-debian-9-connection-problem-4175623357/#post5817508 apt-get install xorgxrdp-hwe-18.04 Couldn't find the package... This lead was promising as it applies to 18.04.02 HWE, which is what I'm running https:/samples/binwww.nakivo.com/x86_64blog/how-to-use-remote-desktop-connection-ubuntu-linux-walkthrough/release dpkg -l |grep xserver-xorg-core ii xserver-xorg-core 2:1.19.6-1ubuntu4.3 amd64 Xorg X server - core server Which seems ok, despite having a problem with XRDP and Ubuntu 18.04 HWE documented very clearly here: http://c-nergy.be/blog/?p=13972 There is clearly an issue with Ubuntu 18.04 and XRDP.The solution seems to be to downgrade xserver-xorg-core and some related packages, which can be done with an install script (https://deviceQueryc-nergy.be/blog/?p=13933) or manually. But I don't want to do that, so I removed xrdp and went back to VNC! apt remove xrdp  CUDA Device Query ===Other Software=== I installed the community edition of PyCharm: snap install pycharm-community --classic #Restart the local terminal so that it has updated paths (Runtime APIafter a snap install, etc.) version /snap/pycharm-community/214/bin/pycharm.sh On launch, you get some config options. I chose to install and enable:*IdeaVim (CUDART static linkinga VI editor emulator) cudaGetDeviceCount returned 100*R*AWS Toolkit Make a launcher: In /usr/share/applications: vi pycharm.desktop [Desktop Entry] Version=2020.2.3 Type=Application Name=PyCharm Icon=/snap/pycharm-community/214/bin/pycharm.png Exec="/snap/pycharm-> no CUDAcommunity/214/bin/pycharm.sh" %f Comment=The Drive to Develop Categories=Development;IDE; Terminal=false StartupWMClass=jetbrains-capable device is detectedpycharm Also, create a launcher on the desktop with the same info. Note that when I came back to the box the launcher didn't work...  Result = FAIL=== MATLAB ====
I installed MATLAB R2024a by downloading the zip, running sudo ./mnistCUDNN cudnnGetVersion() : 7501 , CUDNN_VERSION from cudnn.h : 7501 (7.5.1) Cuda failurer version : GCC 7.4.0 Error: no CUDA-capable device is detected error_util.h:93 Aborting...install
And as researcher: cd and using the defaults of /homeusr/researcherlocal/ source ./venv/binMATLAB/activate python -c "import tensorflow as tf; tf.enable_eager_execution(); print(tf.reduce_sum(tf.random_normal([1000, 1000])))" ..R2024 etc. failed call to cuInit: CUDA_ERROR_NO_DEVICE: no CUDA-capable device The license number is detected ..41201644.kernel driver does not appear to be running on this host (bastard): /proc/driver/nvidia/version does not exist
lspci -vk shows Kernel modules: nvidiafb, nouveau and no Kernel driver in use.===Upgrading the nVIDIA Drivers===
It looks like nouveau In MATLAB, I ran: gpuDevice Error using gpuDevice (line 26) Graphics driver is still blacklisted in /etc/modprobe.d/blacklist-nouveauout of date.conf Download and /usr/bin/nvidia-persistenced --verbose is still being called in /etc/rc.local. ubuntu-drivers devicesreturns exactly what it did before we installed CUDA 10.1 too..install the latest graphics driver for your GPU from NVIDIA.
There is no /proc/driver/nvidia folder, and therefore no /proc/Some quick checks showed that I was using driver/nvidia/version file found. We get the following: /usr/bin/nvidia-persistenced --verbose nvidia-persistenced failed to initialize. Check syslog for more details. tail /var/log/syslog .430.26 on ubuntu 18.Jul 9 13:35:56 bastard kernel: [ 531404.526960] pcieport 0000:00:02.0: [12] Replay Timer Timeout ...Jul 9 13:35:56 bastard nvidia-persistenced: Failed to query NVIDIA devices. Please ensure that the NVIDIA device files (/dev/nvidia*) exist, and that user 0 has read and write permissions for those files. ls /dev/ ...reveals no nvidia devices
nvidia-smi
...NVIDIAlsb_release -SMI has failed because it couldn't communicate with the NVIDIA driver. Make sure that the latest NVIDIA driver is installed and running.a
grep nvidia /etc/modprobe.d/I couldn't quite get MATLAB to tell me what I needed:* https:/lib/modprobe.d/* .www.mathworks.com/etchelp/modprobe.dparallel-computing/blacklistgpu-framebuffercomputing-requirements.confhtml* https:blacklist nvidiafb .//www.mathworks.com/etchelp/modprobe.dparallel-computing/nvidiarun-mex-functions-installercontaining-disablecuda-nouveaucode.conf:html# generated by nvidiamw_20acaa78-994d-4695-ab4b-installerbca1cfc3dbac
Am going to try uninstalling CUDA For MEX, I have 10.1 2 and need 12.2 of the current Nvidia driver, and then reinstalling CUDA 10toolkit: MATLAB Release CUDA Toolkit Version R2024a 12.02 /usr/local/cuda-10.1/bin/cuda-uninstaller.. nvidia-uninstallR2020b 10.2
WARNINGHowever: Your driver installation has been altered since it was initially installed; this may happen, for example, if you have since installed * nVidia said the NVIDIA driver through a mechanism other than nvidia-installer (such as your distribution's native package management system)latest version was https://www. nvidia-installer will attempt to uninstall as best it can. Please see the file 'com/varDownload/logdriverResults.aspx/nvidia230357/en-uninstall.log' us/* The repo said the highest version for details18. WARNING04 is 545: https: Failed to delete some directories//launchpad. See net/~graphics-drivers/var+archive/logubuntu/nvidia-uninstall.log for details. Uninstallation of existing driver: NVIDIA Accelerated Graphics Driver for Linux-x86_64 (418.67) is complete.ppa
Then download cuda_10.0.130_410.48_linux.run from httpsAs root://developer.nvidia.com/cuda runlevel #5 systemctl get-10default #graphical.0target systemctl set-downloaddefault multi-archive?target_os=Linux&target_arch=x86_64&target_distro=Ubuntu&target_version=1804&target_type=runfilelocal, as well as cuda_10.0.130.1_linux.runuser.target systemctl reboot
As ed: sudo suvncserver -kill :2 Killing Xtightvnc process ID 1844  cd /bulk/installAs root: #sh ./cuda_10.0NVIDIA-Linux-x86_64-550.130_410107.48_linux02.run accept all defaults and # The distribution-provided pre-install everything (including 410script failed! #cat /var/log/nvidia-installer.something NVIDIA driver)log
=========== Driver: Installed Toolkit: Installed in /usr/local/cudaapt-10.0get update Samples: Installed in /home/ed, but missing recommended libraries Please make sure that apt install nvidia- PATH includes /usr/local/cudadriver-10.0/bin - LD_LIBRARY_PATH includes /usr/local/cuda-10.0/lib64, or, add /usr/local/cuda-10.0/lib64 to /etc/ld.so.conf and run ldconfig as root To uninstall the CUDA Toolkit, run the uninstall script in /usr/local/cuda-10.0/bin To uninstall the NVIDIA Driver, run nvidia-uninstall 545 Please see CUDA_Installation_Guide_Linux.pdf in /usr/local/cudasystemctl set-10.0/doc/pdf for detailed information on setting up CUDAdefault graphical.target Logfile is /tmp/cuda_install_8524.logsystemctl reboot
Fix the paths:Run MATLAB export PATH=/usr/local/cuda-10.0/bin${PATHgpuDevice Name:+'NVIDIA TITAN RTX' Index:${PATH}}1 export LD_LIBRARY_PATH=/usr/local/cuda-10 ComputeCapability: '7.0/lib64${LD_LIBRARY_PATH5' GraphicsDriverVersion:+'545.29.06' ToolkitVersion:${LD_LIBRARY_PATH}}12.2000
Also gpuDevice(2) vi /etc/ld Name: 'NVIDIA TITAN Xp' Index: 2 ComputeCapability: '6.so.conf1' SupportsDouble: 1 GraphicsDriverVersion: '545.d/cuda29.conf06' /usr/local/cuda-10 ToolkitVersion: 12.0/lib64 ldconfig 2000
FinallyThe messages were: apt install nvidia-driver-545 The following additional packages will be installed: libnvidia-cfg1-545 libnvidia-common-545 libnvidia-compute-545 libnvidia-compute-545:i386 libnvidia-decode-545 libnvidia-decode-545:i386 libnvidia-encode-545 libnvidia-encode-545:i386 libnvidia-extra-545 libnvidia-fbc1-545 libnvidia-fbc1-545:i386 libnvidia-gl-545 libnvidia-gl-545:i386 nvidia-compute-utils-545 nvidia-dkms-545 nvidia-firmware-545-545./cuda_1029.006 nvidia-kernel-common-545 nvidia-kernel-source-545 nvidia-utils-545 xserver-xorg-video-nvidia-545 The following packages will be REMOVED: libnvidia-cfg1-430 libnvidia-common-430 libnvidia-compute-430 libnvidia-compute-430:i386 libnvidia-decode-430 libnvidia-decode-430:i386 libnvidia-encode-430 libnvidia-encode-430:i386 libnvidia-fbc1-430 libnvidia-fbc1-430:i386 libnvidia-gl-430 libnvidia-gl-430:i386 libnvidia-ifr1-430 libnvidia-ifr1-430:i386 nvidia-compute-utils-430 nvidia-dkms-430 nvidia-driver-430 nvidia-kernel-common-430 nvidia-kernel-source-430 nvidia-utils-430 xserver-xorg-video-nvidia-430 The following NEW packages will be installed: libnvidia-cfg1-545 libnvidia-common-545 libnvidia-compute-545 libnvidia-compute-545:i386 libnvidia-decode-545 libnvidia-decode-545:i386 libnvidia-encode-545 libnvidia-encode-545:i386 libnvidia-extra-545 libnvidia-fbc1-545 libnvidia-fbc1-545:i386 libnvidia-gl-545 libnvidia-gl-545:i386 nvidia-compute-utils-545 nvidia-dkms-545 nvidia-driver-545 nvidia-firmware-545-545.13029.106 nvidia-kernel-common-545 nvidia-kernel-source-545 nvidia-utils-545 xserver-xorg-video-nvidia-545 0 upgraded, 21 newly installed, 21 to remove and 2 not upgraded.run accept all defaults

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