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In computing, CUDA is a proprietary [1] 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.
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.
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 ...
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]
The Ada Lovelace architecture follows on from the Ampere architecture that was released in 2020. The Ada Lovelace architecture was announced by Nvidia CEO Jensen Huang during a GTC 2022 keynote on September 20, 2022 with the architecture powering Nvidia's GPUs for gaming, workstations and datacenters.
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 ...
CuPy supports Nvidia CUDA GPU platform, and AMD ROCm GPU platform starting in v9.0. [ 4 ] [ 5 ] CuPy has been initially developed as a backend of Chainer deep learning framework, and later established as an independent project in 2017.
There are three GPU rendering modes: CUDA, which is the preferred method for older Nvidia graphics cards; OptiX, which utilizes the hardware ray-tracing capabilities of Nvidia's Turing architecture & Ampere architecture; HIP, which supports rendering on AMD Radeon graphics cards; and oneAPI for Intel and Intel Arc GPUs. The toolkit software ...