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aptitude is a front end to APT, the Debian package manager. [4] It displays a list of software packages and allows the user to interactively pick packages to install or remove. It has a search system utilizing flexible search patterns. It was initially created for Debian, but has appeared in RPM-based distributions as well.
Advanced Package Tool (APT) is a free-software user interface that works with core libraries to handle the installation and removal of software on Debian and Debian-based Linux distributions. [4] APT simplifies the process of managing software on Unix-like computer systems by automating the retrieval, configuration and installation of software ...
Inherited from the design of Nix, most of the content of the package manager is kept in a directory /gnu/store where only the Guix daemon has write-access. This is achieved via specialised bind mounts, where the Store as a file system is mounted read only, prohibiting interference even from the root user, while the Guix daemon remounts the Store as read/writable in its own private namespace.
The initial CUDA SDK was made public on 15 February 2007, for Microsoft Windows and Linux. Mac OS X support was later added in version 2.0, [17] which supersedes the beta released February 14, 2008. [18] CUDA works with all Nvidia GPUs from the G8x series onwards, including GeForce, Quadro and the Tesla line. CUDA is compatible with most ...
Windows Subsystem for Linux (WSL) is a feature of Microsoft Windows that allows for using a Linux environment without the need for a separate virtual machine or dual booting. WSL is installed by default in Windows 11. [ 2 ]
Pip's command-line interface allows the install of Python software packages by issuing a command: pip install some-package-name. Users can also remove the package by issuing a command: pip uninstall some-package-name. pip has a feature to manage full lists of packages and corresponding version numbers, possible through a "requirements" file. [14]
Learn how to download and install or uninstall the Desktop Gold software and if your computer meets the system requirements.
CUDA code runs on both the central processing unit (CPU) and graphics processing unit (GPU). NVCC separates these two parts and sends host code (the part of code which will be run on the CPU) to a C compiler like GNU Compiler Collection (GCC) or Intel C++ Compiler (ICC) or Microsoft Visual C++ Compiler, and sends the device code (the part which will run on the GPU) to the GPU.