Tegra 2 Ubuntu Driver
The CUDA development environment relies on tight integration with the host development environment, including the host compiler and C runtime libraries, and is therefore only supported on distribution versions that have been qualified for this CUDA Toolkit release.
tegra 2 ubuntu driver
The CUDA Driver requires that the kernel headers and development packages for the running version of the kernel be installed at the time of the driver installation, as well whenever the driver is rebuilt. For example, if your system is running kernel version 3.17.4-301, the 3.17.4-301 kernel headers and development packages must also be installed.
While the Runfile installation performs no package validation, the RPM and Deb installations of the driver will make an attempt to install the kernel header and development packages if no version of these packages is currently installed. However, it will install the latest version of these packages, which may or may not match the version of the kernel your system is using. Therefore, it is best to manually ensure the correct version of the kernel headers and development packages are installed prior to installing the CUDA Drivers, as well as whenever you change the kernel version.
The driver relies on an automatically generated xorg.conf file at /etc/X11/xorg.conf. If a custom-built xorg.conf file is present, this functionality will be disabled and the driver may not work. You can try removing the existing xorg.conf file, or adding the contents of /etc/X11/xorg.conf.d/00-nvidia.conf to the xorg.conf file. The xorg.conf file will most likely need manual tweaking for systems with a non-trivial GPU configuration.
Satisfy DKMS dependency: The NVIDIA driver RPM packages depend on other external packages, such as DKMS and libvdpau. Those packages are only available on third-party repositories, such as EPEL. Any such third-party repositories must be added to the package manager repository database before installing the NVIDIA driver RPM packages, or missing dependencies will prevent the installation from proceeding.
These instructions must be used if you are installing in a WSL environment. Do not use the Ubuntu instructions in this case; it is important to not install the cuda-drivers packages within the WSL environment.
The cuda package installs all the available packages for native developments. That includes the compiler, the debugger, the profiler, the math libraries, and so on. For x86_64 platforms, this also includes Nsight Eclipse Edition and the visual profilers. It also includes the NVIDIA driver package.
32-bit compilation native and cross-compilation is removed from CUDA 12.0 and later Toolkit. Use the CUDA Toolkit from earlier releases for 32-bit compilation. CUDA Driver will continue to support running existing 32-bit applications on existing GPUs except Hopper. Hopper does not support 32-bit applications. Ada will be the last architecture with driver support for 32-bit applications.
Open-source - published kernel modules that are dual licensed MIT/GPLv2. These are new starting in release 515. With every driver release, the source code to the open kernel modules will be published on -gpu-kernel-modules and a tarball will be provided on
When using precompiled drivers, a plugin for the dnf package manager is enabled that cleans up stale .ko files. To prevent system breakages, the NVIDIA dnf plugin also prevents upgrading to a kernel for which no precompiled driver yet exists. This can delay the application of security fixes but ensures that a tested kernel and driver combination is always used. A warning is displayed by dnf during that upgrade situation:
The reboot is required to completely unload the Nouveau drivers and prevent the graphical interface from loading. The CUDA driver cannot be installed while the Nouveau drivers are loaded or while the graphical interface is active.
If installing the driver, the installer will also ask if the openGL libraries should be installed. If the GPU used for display is not an NVIDIA GPU, the NVIDIA openGL libraries should not be installed. Otherwise, the openGL libraries used by the graphics driver of the non-NVIDIA GPU will be overwritten and the GUI will not work. If performing a silent installation, the --no-opengl-libs option should be used to prevent the openGL libraries from being installed. See the Advanced Options section for more details.
Check that the device files/dev/nvidia* exist and have the correct (0666) file permissions. These files are used by the CUDA Driver to communicate with the kernel-mode portion of the NVIDIA Driver. Applications that use the NVIDIA driver, such as a CUDA application or the X server (if any), will normally automatically create these files if they are missing using the setuidnvidia-modprobe tool that is bundled with the NVIDIA Driver. However, some systems disallow setuid binaries, so if these files do not exist, you can create them manually by using a startup script such as the one below:
Required for any silent installation. Performs an installation with no further user-input and minimal command-line output based on the options provided below. Silent installations are useful for scripting the installation of CUDA. Using this option implies acceptance of the EULA. The following flags can be used to customize the actions taken during installation. At least one of --driver, --uninstall, and --toolkit must be passed if running with non-root permissions.
Because of the addition of new features specific to the NVIDIA POWER9 CUDA driver, there are some additional setup requirements in order for the driver to function properly. These additional steps are not handled by the installation of CUDA packages, and failure to ensure these extra requirements are met will result in a non-functional CUDA driver installation.
Disable a udev rule installed by default in some Linux distributions that cause hot-pluggable memory to be automatically onlined when it is physically probed. This behavior prevents NVIDIA software from bringing NVIDIA device memory online with non-default settings. This udev rule must be disabled in order for the NVIDIA CUDA driver to function properly on POWER9 systems.
NVIDIA is providing a user-space daemon on Linux to support persistence of driver state across CUDA job runs. The daemon approach provides a more elegant and robust solution to this problem than persistence mode. For more details on the NVIDIA Persistence Daemon, see the documentation here.
If you installed the driver, verify that the correct version of it is loaded. If you did not install the driver, or are using an operating system where the driver is not loaded via a kernel module, such as L4T, skip this step.
System updates may include an updated Linux kernel. In many cases, a new Linux kernel will be installed without properly updating the required Linux kernel headers and development packages. To ensure the CUDA driver continues to work when performing a system update, rerun the commands in the Kernel Headers and Development Packages section.
To install a CUDA driver at a version earlier than 367 using a network repo, the required packages will need to be explicitly installed at the desired version. For example, to install 352.99, instead of installing the cuda-drivers metapackage at version 352.99, you will need to install all required packages of cuda-drivers at version 352.99.
If it runs Android, it has Linux drivers, since Android runs on a Linux kernel. However Google maintains its own forked version of the Linux kernel source, and not all drivers have been ported back. There is no official Ubuntu distribution for ARM, but there are people working on an informal ARM port. That page lists OMAP chips but not Tegra. There is a Tegra porting effort (for the Toshiba AC100) as well, but it's not completely working. If you don't find what you're looking for, try Debian, which officially supports ARM (but doesn't support recent tablets out-of-the-box either).
Android is based on a Linux kernel, but it lacks a few kernel features, and the userland is completely different. The advantage of Android is that it'll have all the drivers you need. The main downsides are that it's difficult to find Android applications that are meant for offline work, and that the user interface is intended for small screens with only full-screen windows. Nonetheless, you can install many development tools on Android, including BusyBox (basic command-line tools), scripting languages (Perl, Python, Lua, Ruby, ...), but GUI applications are a problem since Android doesn't use X. You'll need to find an Android editor that suits you, and so on.
There are many ARM-based devices running Linux natively and even more that could. Yes, the drivers are often a problem - just as it was the case in the early years of Linux running on common PC desktops. So you should always dig into the subject of compatibility with particular device.
Tegra is a system on a chip (SoC) series developed by Nvidia for mobile devices such as smartphones, personal digital assistants, and mobile Internet devices. The Tegra integrates an ARM architecture central processing unit (CPU), graphics processing unit (GPU), northbridge, southbridge, and memory controller onto one package. Early Tegra SoCs are designed as efficient multimedia processors. The Tegra-line evolved to emphasize performance for gaming and machine learning applications without sacrificing power efficiency, before taking a drastic shift in direction towards platforms that provide vehicular automation with the applied "Drive" brand name on reference boards and its semiconductors; and with the "Jetson" brand name for boards adequate for AI applications within e.g. robots or drones, and for various smart high level automation purposes. 350c69d7ab