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Nvidia VDPAU Feature Sets [32] are different hardware generations of GPU's supporting different levels of (Nvidia PureVideo) hardware decoding capabilities. For feature sets A, B and C, the maximum video width and height are 2048 pixels , minimum width and height 48 pixels, and all codecs are currently limited to a maximum of 8192 macroblocks ...
CUDA 9.0–9.2 comes with these other components: CUTLASS 1.0 – custom linear algebra algorithms, NVIDIA Video Decoder was deprecated in CUDA 9.2; it is now available in NVIDIA Video Codec SDK; CUDA 10 comes with these other components: nvJPEG – Hybrid (CPU and GPU) JPEG processing; CUDA 11.0–11.8 comes with these other components: [20 ...
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.
Pop!_OS 20.10 was released on 23 October 2020 and is based upon Ubuntu 20.10. It introduced stackable tiled windows and floating window exceptions in auto-tiling mode. It introduced stackable tiled windows and floating window exceptions in auto-tiling mode.
The source code is available in the Nvidia Linux driver downloads on systems that support nvidia-uvm.ko. In May 2022, Nvidia announced a new initiative and policy to open source its GPU Loadable Kernel Modules with dual GPL/MIT license, but only new models at alpha quality. But said "These changes are for the kernel modules, while the user-mode ...
Nvidia's Tegra K1 (codenamed "Logan") features ARM Cortex-A15 cores in a 4+1 configuration similar to Tegra 4, or Nvidia's 64-bit Project Denver dual-core processor as well as a Kepler graphics processing unit with support for Direct3D 12, OpenGL ES 3.1, CUDA 6.5, OpenGL 4.4/OpenGL 4.5, and Vulkan.
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.
2017-05-10: Mesa 17.1 OpenGL 4.2+ for Intel Ivy Bridge (more than Intel driver for Windows, OpenGL 3.3+ for Intel Open SWR Rasterizer (important for cluster Computer for huge simulations) 2017-12-08: Mesa 17.3 AMD Vulkan Driver RADV full compliant in Khronos Test of Vulkan 1.0