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WSL beta was introduced in Windows 10 version 1607 (Anniversary Update) on August 2, 2016. Only Ubuntu (with Bash as the default shell) was supported. WSL beta was also called "Bash on Ubuntu on Windows" or "Bash on Windows". WSL was no longer beta in Windows 10 version 1709 (Fall Creators Update), released on October 17, 2017.
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, [18] which supersedes the beta released February 14, 2008. [19] CUDA works with all Nvidia GPUs from the G8x series onwards, including GeForce, Quadro and the Tesla line. CUDA is compatible with most ...
The libvdpau standalone VDPAU library is distributed by Nvidia independently of their proprietary Linux graphics driver in an effort to help the adoption of VDPAU by those outside of Nvidia. This open source library package contains a wrapper library and a debugging library allowing other manufacturers to implement VDPAU in their device drivers.
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.
For instance, a base image could contain a fresh installation of a known working operating system, and overlay images can be used to record changes. Should the guest system become unusable (through virus attack, accidental system destruction, etc.), the user can delete the overlay and use an earlier emulated disk image.
Free and open-source drivers are primarily developed on and for Linux by Linux kernel developers, third-party programming enthusiasts and employees of companies such as Advanced Micro Devices. Each driver has five parts: A Linux kernel component DRM; A Linux kernel component KMS driver (the display controller driver)
rCUDA, which stands for Remote CUDA, is a type of middleware software framework for remote GPU virtualization. Fully compatible with the CUDA application programming interface ( API ), it allows the allocation of one or more CUDA-enabled GPUs to a single application.
OpenCL (Open Computing Language) is a framework for writing programs that execute across heterogeneous platforms consisting of central processing units (CPUs), graphics processing units (GPUs), digital signal processors (DSPs), field-programmable gate arrays (FPGAs) and other processors or hardware accelerators.