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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.
The Nvidia CUDA Compiler (NVCC) translates code written in CUDA, a C++-like language, into PTX instructions (an assembly language represented as American Standard Code for Information Interchange text), and the graphics driver contains a compiler which translates PTX instructions into executable binary code, [2] which can run on the processing ...
developer.nvidia.com /cuda-zone In computing , CUDA is a proprietary [ 2 ] parallel computing platform and application programming interface (API) that allows software to use certain types of graphics processing units (GPUs) for accelerated general-purpose processing, an approach called general-purpose computing on GPUs.
Nvidia OptiX (OptiX Application Acceleration Engine) is a ray tracing API that was first developed around 2009. [1] The computations are offloaded to the GPUs through either the low-level or the high-level API introduced with CUDA. CUDA is only available for Nvidia's graphics products. Nvidia OptiX is part of Nvidia GameWorks. OptiX is a high ...
PGI (formerly The Portland Group, Inc.) was a company that produced a set of commercially available Fortran, C and C++ compilers for high-performance computing systems. On July 29, 2013, Nvidia acquired The Portland Group, Inc. [1] [2] As of August 5, 2020, the "PGI Compilers and Tools" technology is a part of the Nvidia HPC SDK product available as a free download from Nvidia.
In the middle: the FOSS stack, composed out of DRM & KMS driver, libDRM and Mesa 3D.Right side: Proprietary drivers: Kernel BLOB and User-space components. nouveau (/ n uː ˈ v oʊ /) is a free and open-source graphics device driver for Nvidia video cards and the Tegra family of SoCs written by independent software engineers, with minor help from Nvidia employees.
CuPy is an open source library for GPU-accelerated computing with Python programming language, providing support for multi-dimensional arrays, sparse matrices, and a variety of numerical algorithms implemented on top of them. [3]
In February 2009, CoreCodec released an update to CoreAVC that implemented support for Nvidia CUDA. CUDA allows selected Nvidia graphics cards to assist in the decoding of video. In March 2011, CoreCodec introduced support for DXVA. Like CUDA, DXVA allows ATI and NVIDIA based graphics cards to assist in the decoding of video. [1]