Changes

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].

<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>

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.

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

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.

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

Driver: Installed Toolkit: Installed in /usr/local/cuda- Install the CUDA 10.1/0 Toolkit? Samples: Installed in (y)es/home(n)o/ed/, but missing recommended libraries(q)uit: y

Please make sure that Enter Toolkit Location - PATH includes /usr/local/cuda-10.1/bin - LD_LIBRARY_PATH includes /usr/local/cuda-10.1/lib64, or, add [ default is /usr/local/cuda-10.1/lib64 to /etc/ld.so.conf and run ldconfig as root0 ]:

To uninstall the CUDA Toolkit, run cuda-uninstaller in Do you want to install a symbolic link at /usr/local/cuda-10.1? (y)es/(n)o/bin To uninstall the NVIDIA Driver, run nvidia-uninstall(q)uit: y

Install the CUDA 10.0 Samples? (y)es/(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/cuda_install_2807.log Now fix the paths. To do this for a single user do: export PATH=/usr/local/cuda-installer10.0/bin:/usr/local/cuda-10.0${PATH:+:${PATH}} export LD_LIBRARY_PATH=/usr/local/cuda-10.log0/lib64${LD_LIBRARY_PATH:+:${LD_LIBRARY_PATH}}

Fix the pathsBut it is better to fix it for everyone by editing your environment file: export vi /etc/environment PATH="/usr/local/cuda-10.10/bin:/usr/local/cuda-10.1sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/NsightCompute-2019.1${PATHbin:+/usr/games:${PATH}}/usr/local/games" export LD_LIBRARY_PATH="/usr/local/cuda-10.10/lib64${LD_LIBRARY_PATH:+:${LD_LIBRARY_PATH}}"

Start With version cuda 10.0, you don't need to edit rc.local to start the persistence daemon:

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

Make the samples in:... cd /usr/local/cuda-10.10/samples

Change into the sample directory and run the tests: cd /usr/local/cuda-10.10/samples/bin/x86_64/linux/release

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.

Then follow https://github.com/NVIDIA/nvidia-docker#quick-start to install docker2, but change the last command to use cuda 10.10

docker run --runtime=nvidia --rm nvidia/cuda:10.10-base nvidia-smi

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

==Video Driver Issue=VNC===

After logging into In order to use the box sometime latergraphical interface for Matlab and other applications, it seems that the video drivers are no longer loading, presumably as we need a consequence of some update or somethingVNC server.

nvidiaNow install TightVNC, following the instructions: https://www.digitalocean.com/community/tutorials/how-settings to-install-query FlatpanelNativeResolution ERROR: NVIDIA driver is not loadedand-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/localbin/cudavncserver -10.kill :%i > /dev/null 2>&1 ExecStart=/samplesusr/bin/x86_64vncserver -depth 24 -geometry 1280x800 :%i ExecStop=/usr/linuxbin/releasevncserver -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/deviceQuerytunnel-vnc-over-ssh/ ====Connection Issues==== CUDA Device Query 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 (Runtime APIit was 5901) version and not firewalled using the listening ports tab under network on resmon.exe (CUDART static linkingit said allowed, not restricted under firewall status). VNC seemed to be running fine on Bastard, and I tried connecting to localhost::1 (that is 5901 on the localhost, through 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: netstat -tlpn tcp 0 0 0.0.0.0:5902 0.0.0.0:* LISTEN 2025/Xtightvnc ufw status Status: inactive The localhost port seems to be open and listening just fine: 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: cudaGetDeviceCount returned 100ExecStart=/usr/bin/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 -> no CUDATerminal 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/error-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. https://www.linuxquestions.org/questions/linux-software-2/xrdp-under-debian-9-connection-problem-4175623357/#post5817508 apt-get install xorgxrdp-hwe-capable device 18.04 Couldn't find the package... This lead was promising as it applies to 18.04.02 HWE, which is detectedwhat I'm running https://www.nakivo.com/blog/how-to-use-remote-desktop-connection-ubuntu-linux-walkthrough/ 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 Result 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://c-nergy.be/blog/?p= FAIL13933) or manually. But I don't want to do that, so I removed xrdp and went back to VNC! apt remove xrdp

And as researcherI installed the community edition of PyCharm: cd /home/researcher/ source ./venv/bin/activatesnap install pycharm-community --classic python -c "import tensorflow as tf; tf.enable_eager_execution #Restart the local terminal so that it has updated paths (); print(tfafter a snap install, etc.reduce_sum(tf.random_normal([1000, 1000])))" ... failed call to cuInit: CUDA_ERROR_NO_DEVICE: no CUDA/snap/pycharm-capable device is detected ...kernel driver does not appear to be running on this host (bastard): community/proc214/driverbin/nvidia/version does not existpycharm.sh

lspci -vk shows Kernel modules: nvidiafbOn launch, nouveau you get some config options. I chose to install and no Kernel driver in use.enable:*IdeaVim (a VI editor emulator)*R*AWS Toolkit

It looks like nouveau is still blacklisted in Make a launcher: In /etcusr/share/modprobeapplications: vi pycharm.desktop [Desktop Entry] Version=2020.2.d3 Type=Application Name=PyCharm Icon=/snap/blacklistpycharm-nouveau.conf and community/usr214/bin/nvidiapycharm.png Exec="/snap/pycharm-persistenced --verbose is still being called in community/214/etcbin/rcpycharm.local. ubuntush" %f Comment=The Drive to Develop Categories=Development;IDE; Terminal=false StartupWMClass=jetbrains-drivers devicesreturns exactly what it did before we installed CUDA 10.1 too...pycharm

There is no /proc/driver/nvidia folderAlso, and therefore no /proc/driver/nvidia/version file found. We get create a launcher on the following: /usr/bin/nvidia-persistenced --verbose nvidia-persistenced failed to initialize. Check syslog for more details. tail /var/log/syslog ...Jul 9 13:35:56 bastard kernel: [ 5314.526960] 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 ...NVIDIA-SMI has failed because it couldn't communicate desktop with the NVIDIA driver. Make sure that the latest NVIDIA driver is installed and runningsame info.

grep nvidia /etc/modprobeNote that when I came back to the box the launcher didn't work.d/* /lib/modprobe.d/* .../etc/modprobe.d/blacklist-framebuffer.conf:blacklist nvidiafb .../etc/modprobe.d/nvidia-installer-disable-nouveau.conf:# generated by nvidia-installer

===Uninstall/Reinstall= MATLAB ====

Am going to try uninstalling CUDA 10.1 and I installed MATLAB R2024a by downloading the current Nvidia driverzip, and then reinstalling CUDA 10.0running /usr/local/cuda-10sudo .1/bin/cuda-uninstaller nvidia-uninstallinstall

WARNING: Your driver installation has been altered since it was initially installed; this may happen, for example, if you have since installed and using the NVIDIA driver through a mechanism other than nvidia-installer (such as your distribution's native package management system). nvidia-installer will attempt to uninstall as best it can. Please see the file '/var/logdefaults of /nvidia-uninstall.log' for details. WARNING: Failed to delete some directories. See usr/varlocal/logMATLAB/nvidia-uninstall.log for details. Uninstallation of existing driver: NVIDIA Accelerated Graphics Driver for Linux-x86_64 (418R2024 etc.67) The license number is complete41201644.

Then download cuda_10.0.130_410.48_linux.run from https://developer.nvidia.com/cuda-10.0-download-archive?target_os=Linux&target_arch=x86_64&target_distro=Ubuntu&target_versionUpgrading the nVIDIA Drivers==1804&target_type=runfilelocal, as well as cuda_10.0.130.1_linux.run.

In MATLAB, I ran: sudo sugpuDevice cd /bulk/install Error using gpuDevice (line 26) ./cuda_10.0.130_410 Graphics driver is out of date.48_linux.run accept all defaults Download and install everything (including 410the latest graphics driver for your GPU from NVIDIA.something NVIDIA driver)

=========== Driver: Installed Toolkit: Installed in /usr/local/cuda-10.0 Samples: Installed in /home/ed, but missing recommended libraries Please make sure Some quick checks showed that - PATH includes /usr/local/cuda-10I was using driver version 430.0/bin - LD_LIBRARY_PATH includes /usr/local/cuda-10.0/lib64, or, add /usr/local/cuda-1026 on ubuntu 18.0/lib64 to /etc/ld04.so02.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-uninstallsmi Please see CUDA_Installation_Guide_Linux.pdf in /usr/local/cudalsb_release -10.0/doc/pdf for detailed information on setting up CUDA. Logfile is /tmp/cuda_install_8524.loga

Fix the pathsI couldn't quite get MATLAB to tell me what I needed: export PATH=* https://usrwww.mathworks.com/localhelp/cudaparallel-computing/gpu-computing-10requirements.0html* https:/bin${PATH:+:${PATH}} export LD_LIBRARY_PATH=/usrwww.mathworks.com/help/localparallel-computing/run-mex-functions-containing-cuda-10code.0/lib64${LD_LIBRARY_PATH:+:${LD_LIBRARY_PATH}}html#mw_20acaa78-994d-4695-ab4b-bca1cfc3dbac

AlsoFor MEX, I have 10.2 and need 12.2 of the CUDA toolkit: MATLAB Release CUDA Toolkit Version vi /etc/ldR2024a 12.so2 .conf.d/cuda.conf /usr/local/cuda- R2020b 10.0/lib64 ldconfig 2

FinallyHowever: * nVidia said the latest version was https://www.nvidia.com/Download/cuda_10driverResults.0aspx/230357/en-us/* The repo said the highest version for 18.13004 is 545: https://launchpad.1.run accept all defaultsnet/~graphics-drivers/+archive/ubuntu/ppa

Unfortunately this didn't work. After a rebootAs root: nvidiarunlevel #5 systemctl get-settings default #graphical.target systemctl set-default multi-query FlatpanelNativeResolutionuser.target Unable to init server: Could not connect: Connection refused (message was same as before on the box, this was over ssh)systemctl reboot

./deviceQuery Starting... CUDA Device Query (Runtime API) version (CUDART static linking)As ed: cudaGetDeviceCount returned 35 vncserver -> CUDA driver version is insufficient for CUDA runtime versionkill :2 Result = FAIL Killing Xtightvnc process ID 1844

python -c "import tensorflow as tf; tf.enabl e_eager_execution(); As root: print(tf#sh .reduce_sum(tf.random_normal([1000, 1000])))" 2019/NVIDIA-Linux-07x86_64-09 15:20:40550.107.085877: E tensorflow/stream_executor/cuda/cuda_driver02.cc:300 run ] failed call to cuInit: CUDA_ERROR_NO_DEVICE: no CUDA# The distribution-capable device is detecte d 2019provided pre-07-09 15:20:40.085978: I tensorflow/stream_executor/cuda/cuda_diagnostics.c install script failed! c:148] kernel driver does not appear to be running on this host (bastard): #cat /proc var/driverlog/nvidia/version does not exist-installer.log

/usr/bin/apt-get update apt install nvidia-persistenced -driver-verbose545 nvidiasystemctl set-persistenced failed to initialize. Check syslog for more detailsdefault graphical.target systemctl reboot

lspci -vk also returned the same as beforeRun MATLAB gpuDevice Name: 'NVIDIA TITAN RTX' Index: 1 ComputeCapability: '7. This is really frustrating!5' GraphicsDriverVersion: '545.29.06' ToolkitVersion: 12.2000

Did the following gpuDevice(2) Name: 'NVIDIA TITAN Xp' Index: 2 ComputeCapability:'6.1' apt-get install nvidia-prime SupportsDouble: 1 prime-select nvidia GraphicsDriverVersion: '545.29.06' Info ToolkitVersion: the nvidia profile is already set12.2000

The messages were: updateapt install nvidia-initramfs driver-u545 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-545-545.29.06 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-545-545.29.06 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.