Re: Linux Ubuntu Para Pc
Damiane Burgun
Ubuntu flavours offer a unique way to experience Ubuntu, each with their own choice of default applications and settings. Ubuntu flavours are owned and developed by members of our global community and backed by the full Ubuntu archive for packages and updates.
Edubuntu is an official flavour of Ubuntu crafted for use in the education world. Teachers and students will have access to a huge ecosystem of learning software and educational tools built on a familiar and usable desktop. Edubuntu provides a fast, stable, secure and privacy conscious option for schools and universities.
Kubuntu unites Ubuntu with KDE and the Plasma desktop, bringing you a full set of applications including productivity, office, email, graphics, photography, and music applications ready to use at startup with extensive additional software installed from not one, but two desktop package managers.
Lubuntu is designed to be a simple, easy to use system that is light, fast and modern. Lubuntu provides the LXQt desktop environment which is focused on Qt technologies. Lubuntu comes with the essential applications and services needed to browse the Internet, chat, play and be productive.
Ubuntu Cinnamon combines Ubuntu with the Cinnamon desktop, built upon GNOME 2 to provide a traditionally modern experience. It is made for all home users alike, with intuitive software, and a simpler, customisable desktop suited with many personalization options and addons for some extra spice.
The Ubuntu Kylin project is tuned to the needs of Chinese users, providing a thoughtful and elegant experience out-of-the-box. The lightweight Ubuntu Kylin User Interface (UKUI) is perfect for older machines, and an ideal introduction to Linux for first-time users.
Ubuntu MATE is a stable, easy-to-use operating system with a configurable desktop environment. It is ideal for those who want the most out of their computers and prefer a traditional desktop metaphor. With modest hardware requirements it is suitable for modern workstations, single board computers and older hardware alike. Ubuntu MATE makes modern computers fast and old computers usable.
Ubuntu Studio is pre-configured for content creation of all kinds. Whether you're an audio engineer, musician, graphic designer, photographer, video producer, or streamer, this is a full-fledged desktop computing system that will fit your needs. If you can dream it, you can create it with Ubuntu Studio.
Bringing the best of Ubuntu and Unity together, Ubuntu Unity is a beautiful, slick and lightweight Ubuntu flavour. With its beautiful design, efficient and elegant workflow, and features like the heads-up display (HUD), the Global Menu, powerful search and a high level of customizability (using the Unity Tweak Tool), you'll be able to work with an unparalleled level of efficiency. You can also choose from a wide range of window animations and effects available in Compiz.
Xubuntu comes with Xfce, which is a stable, light and configurable desktop environment with a lot of consideration for usability. Whether you have a high-end computer or even a moderately older machine, Xubuntu is able to provide you with a smooth and usable desktop experience. Xubuntu has an expansive list of customization options so you can make the desktop your own.
Download the latest release of Ubuntu desktop, the open source operating system that powers millions of PCs and laptops around the world. It's easy to install on Windows or macOS, or run Ubuntu alongside them!
Provide a small set of extensions to standard programming languages, like C, that enable a straightforward implementation of parallel algorithms. With CUDA C/C++, programmers can focus on the task of parallelization of the algorithms rather than spending time on their implementation.
Support heterogeneous computation where applications use both the CPU and GPU. Serial portions of applications are run on the CPU, and parallel portions are offloaded to the GPU. As such, CUDA can be incrementally applied to existing applications. The CPU and GPU are treated as separate devices that have their own memory spaces. This configuration also allows simultaneous computation on the CPU and GPU without contention for memory resources.
CUDA-capable GPUs have hundreds of cores that can collectively run thousands of computing threads. These cores have shared resources including a register file and a shared memory. The on-chip shared memory allows parallel tasks running on these cores to share data without sending it over the system memory bus.
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.
CUDA support for Ubuntu 20.04.x, Ubuntu 22.04.x, RHEL 8.x, RHEL 9.x, Rocky Linux 8.x, Rocky Linux 9.x, SUSE SLES 15.x and OpenSUSE Leap 15.x will be until the standard EOSS as defined for each OS. Please refer to the support lifecycle for these OSes to know their support timelines.
This document is intended for readers familiar with the Linux environment and the compilation of C programs from the command line. You do not need previous experience with CUDA or experience with parallel computation. Note: This guide covers installation only on systems with X Windows installed.
Many commands in this document might require superuser privileges. On most distributions of Linux, this will require you to log in as root. For systems that have enabled the sudo package, use the sudo prefix for all necessary commands.
The gcc compiler is required for development using the CUDA Toolkit. It is not required for running CUDA applications. It is generally installed as part of the Linux installation, and in most cases the version of gcc installed with a supported version of Linux will work correctly.
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.
This is the version of the kernel headers and development packages that must be installed prior to installing the CUDA Drivers. This command will be used multiple times below to specify the version of the packages to install. Note that below are the common-case scenarios for kernel usage. More advanced cases, such as custom kernel branches, should ensure that their kernel headers and sources match the kernel build they are running.
If you perform a system update which changes the version of the Linux kernel being used, make sure to rerun the commands below to ensure you have the correct kernel headers and kernel development packages installed. Otherwise, the CUDA Driver will fail to work with the new kernel.
GDS is supported in two different modes: GDS (default/full perf mode) and Compatibility mode. Installation instructions for them differ slightly. Compatibility mode is the only mode that is supported on certain distributions due to software dependency limitations.
Starting with CUDA toolkit 12.2.2, GDS kernel driver package nvidia-gds version 12.2.2-1 (provided by nvidia-fs-dkms 2.17.5-1) and above is only supported with the NVIDIA open kernel driver. Follow the instructions in Removing CUDA Toolkit and Driver to remove existing NVIDIA driver packages and then follow instructions in NVIDIA Open GPU Kernel Modules to install NVIDIA open kernel driver packages.
The CUDA Toolkit can be installed using either of two different installation mechanisms: distribution-specific packages (RPM and Deb packages), or a distribution-independent package (runfile packages).
The download can be verified by comparing the MD5 checksum posted at with that of the downloaded file. If either of the checksums differ, the downloaded file is corrupt and needs to be downloaded again.
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.
Before installing CUDA, any previous installations that could conflict should be uninstalled. This will not affect systems which have not had CUDA installed previously, or systems where the installation method has been preserved (RPM/Deb vs. Runfile). See the following charts for specifics.
If matching kernel-headers and kernel-devel packages are not available for the currently running kernel version, you may need to use the previously shipped version of these packages. See _bug.cgi?id=1986132 for more information.
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.
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