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  2. Parallel Thread Execution - Wikipedia

    en.wikipedia.org/wiki/Parallel_Thread_Execution

    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).

  3. Nvidia CUDA Compiler - Wikipedia

    en.wikipedia.org/wiki/Nvidia_CUDA_Compiler

    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.

  4. CUDA - Wikipedia

    en.wikipedia.org/wiki/CUDA

    GPUOpen HIP: A thin abstraction layer on top of CUDA and ROCm intended for AMD and Nvidia GPUs. Has a conversion tool for importing CUDA C++ source. Supports CUDA 4.0 plus C++11 and float16. ZLUDA is a drop-in replacement for CUDA on AMD GPUs and formerly Intel GPUs with near-native performance. [33]

  5. General-purpose computing on graphics processing units

    en.wikipedia.org/wiki/General-purpose_computing...

    The dominant proprietary framework is Nvidia CUDA. [13] Nvidia launched CUDA in 2006, a software development kit (SDK) and application programming interface (API) that allows using the programming language C to code algorithms for execution on GeForce 8 series and later GPUs. ROCm, launched in 2016, is AMD's open-source response to CUDA.

  6. Ada Lovelace (microarchitecture) - Wikipedia

    en.wikipedia.org/wiki/Ada_Lovelace_(micro...

    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.

  7. ROCm - Wikipedia

    en.wikipedia.org/wiki/ROCm

    Nvidia's CUDA is closed-source, whereas AMD ROCm is open source. There is open-source software built on top of the closed-source CUDA, for instance RAPIDS. CUDA is able run on consumer GPUs, whereas ROCm support is mostly offered for professional hardware such as AMD Instinct and AMD Radeon Pro.

  8. OpenACC - Wikipedia

    en.wikipedia.org/wiki/OpenACC

    Nvidia: PGI Compilers & Tools OpenACC Getting Started Guide(2018). Stéphane Ethier: Introduction to GPU programming with OpenACC, Research Computing Bootcamp (November 1st, 2019) OpenACC-standard.org: OpenACC A Complete Guide; Olga Abramkina, Rémy Dubois, Thibaut Véry: OpenACC for GPU: an introduction (Jun,02, 2023)

  9. Nvidia GRID - Wikipedia

    en.wikipedia.org/wiki/Nvidia_GRID

    Nvidia GRID is a family of graphics processing units (GPUs) made by Nvidia, introduced in 2008, that is targeted specifically towards cloud gaming. [1] The Nvidia GRID includes both graphics processing and video encoding into a single device which is able to decrease the input to display latency of cloud based video game streaming . [ 2 ]