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CUDA provides both a low level API (CUDA Driver API, non single-source) and a higher level API (CUDA Runtime API, single-source). 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 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.
CuPy is a part of the NumPy ecosystem array libraries [7] and is widely adopted to utilize GPU with Python, [8] especially in high-performance computing environments such as Summit, [9] Perlmutter, [10] EULER, [11] and ABCI. [12] CuPy is a NumFOCUS sponsored project. [13]
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.
Installation instructions are provided for Linux and Windows in the official AMD ROCm documentation. ROCm software is currently spread across several public GitHub repositories. Within the main public meta-repository , there is an XML manifest for each official release: using git-repo , a version control tool built on top of Git , is the ...
MVC acceleration is OS dependent: it is fully supported in Microsoft Windows through the Microsoft DXVA and Nvidia CUDA APIs, but is not supported through Nvidia's VDPAU API. The fourth generation PureVideo HD is sometimes called "PureVideo HD 4" or VP4, although this is not an official Nvidia designation.
Users must install the Media Feature Pack for Windows, and on Windows Server users must install Media Foundation features. Each RC software license is limited to 32 CPU cores and 3 GPU cards. For higher configurations, more licenses must be purchased equivalently. A computer with 4 CPU cores, 16 GB RAM and 386 CUDA cores is recommended.
VDPAU was originally designed by Nvidia for their PureVideo SIP block present on their GeForce 8 series and later GPUs. [8]On March 9, 2015, Nvidia released VDPAU version 1.0 which supports High Efficiency Video Coding (HEVC) decoding for the Main, Main 4:4:4, Main Still Picture, Main 10, and Main 12 profiles.