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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.
CUDA SDK 8.0 support for Compute Capability 2.0 – 6.x (Fermi, Kepler, Maxwell, Pascal) Last version with support for compute capability 2.x (Fermi)
macOS Monterey drops support for Macs released from 2013 to 2014, [28] [29] including all Macs with Nvidia GPUs. Macs that support macOS Monterey are as follows. iMac (Late 2015 or later) iMac Pro (2017) MacBook (Early 2016 or later) MacBook Air (Early 2015 or later) MacBook Pro (Early 2015 or later) Mac Mini (Late 2014 or later) Mac Pro (Late ...
NVIDIA N15P-GX-A2 GPU of the GeForce 860M with its VRAM. The GeForce 800M series is a family of graphics processing units by Nvidia for laptop PCs. [3] It consists of rebrands of mobile versions of the GeForce 700 series [3] and some newer chips that are lower end compared to the rebrands.
CUDA Compute Capability 8.0 for A100 and 8.6 for the GeForce 30 series [7] TSMC's 7 nm FinFET process for A100; Custom version of Samsung's 8 nm process (8N) for the GeForce 30 series [8] Third-generation Tensor Cores with FP16, bfloat16, TensorFloat-32 (TF32) and FP64 support and sparsity acceleration. [9]