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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 ...
PyTorch Tensors are similar to NumPy Arrays, but can also be operated on a CUDA-capable NVIDIA GPU. PyTorch has also been developing support for other GPU platforms, for example, AMD's ROCm [27] and Apple's Metal Framework. [28] PyTorch supports various sub-types of Tensors. [29]
All models support Direct3D 7 and OpenGL 1.2; All models support TwinView Dual-Display Architecture, Second Generation Transform and Lighting (T&L), Nvidia Shading Rasterizer (NSR), High-Definition Video Processor (HDVP) GeForce2 MX models support Digital Vibrance Control (DVC)
Before Direct3D 10, new versions of the API introduced support for new hardware capabilities, however these capabilities were optional and had to be queried with "capability bits" or "caps". Direct3D 10.1 was the first to use a concept of "feature levels" [ 1 ] [ 3 ] [ 6 ] to support both Direct3D 10.0 and 10.1 hardware.
It also adds support for cube map arrays, separate blend modes per-MRT, coverage mask export from a pixel shader, ability to run pixel shader per sample, access to multi-sampled depth buffers [39] and requires that the video card supports Shader Model 4.1 or higher and 32-bit floating-point operations. Direct3D 10.1 still fully supports ...
Wolfram Mathematica is a software system with built-in libraries for several areas of technical computing that allows machine learning, statistics, symbolic computation, data manipulation, network analysis, time series analysis, NLP, optimization, plotting functions and various types of data, implementation of algorithms, creation of user interfaces, and interfacing with programs written in ...
Julia is a high-level, general-purpose [17] dynamic programming language, still designed to be fast and productive, [18] for e.g. data science, artificial intelligence, machine learning, modeling and simulation, most commonly used for numerical analysis and computational science.
Darwin currently includes support for the 64-bit x86-64 variant of the Intel x86 processors used in Intel-based Macs and the 64-bit ARM processors used in the iPhone 5S and later, the 6th generation iPod Touch, the 5th generation iPad and later, the iPad Air family, the iPad Mini 2 and later, the iPad Pro family, the fourth generation and later ...