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CUDA works with all Nvidia GPUs from the G8x series onwards, including GeForce, Quadro and the Tesla line. CUDA is compatible with most standard operating systems. CUDA 8.0 comes with the following libraries (for compilation & runtime, in alphabetical order): cuBLAS – CUDA Basic Linear Algebra Subroutines library; CUDART – CUDA Runtime library
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 is based upon Ubuntu and its release cycle is the same as Ubuntu, [46] with new releases every six months in April and October. Long-term support releases are made every two years, in April of even-numbered years. Each non-LTS release is supported for three months after the release of the next version, and LTS releases are supported for ...
The Nvidia CUDA Compiler (NVCC) translates code written in CUDA, a C++-like language, into PTX instructions (an assembly language), and the graphics driver contains a compiler which translates PTX instructions into executable binary code, [2] which can run on the processing cores of Nvidia graphics processing units (GPUs).
GNOME Disks is a graphical front-end for udisks. [3] It can be used for partition management, S.M.A.R.T. monitoring, benchmarking, and software RAID (until v. 3.12). [4] An introduction is included in the GNOME Documentation Project.
Nvidia NVDEC (formerly known as NVCUVID [1]) is a feature in its graphics cards that performs video decoding, offloading this compute-intensive task from the CPU. [2] NVDEC is a successor of PureVideo and is available in Kepler and later Nvidia GPUs. It is accompanied by NVENC for video encoding in Nvidia's Video Codec SDK. [2]
Nvidia Tesla C2075. Offering computational power much greater than traditional microprocessors, the Tesla products targeted the high-performance computing market. [4] As of 2012, Nvidia Teslas power some of the world's fastest supercomputers, including Summit at Oak Ridge National Laboratory and Tianhe-1A, in Tianjin, China.
Fat binaries were a feature of NeXT's NeXTSTEP/OPENSTEP operating system, starting with NeXTSTEP 3.1. In NeXTSTEP, they were called "Multi-Architecture Binaries". Multi-Architecture Binaries were originally intended to allow software to be compiled to run both on NeXT's Motorola 68k-based hardware and on Intel IA-32-based PCs running NeXTSTEP, with a single binary file for both platforms. [10]