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  2. CUDA - Wikipedia

    en.wikipedia.org/wiki/CUDA

    CUDA provides both a low level API (CUDA Driver API, non single-source) and a higher level API (CUDA Runtime API, single-source). The initial CUDA SDK was made public on 15 February 2007, for Microsoft Windows and Linux. Mac OS X support was later added in version 2.0, [18] which supersedes the beta released February 14, 2008. [19] CUDA works ...

  3. CuPy - Wikipedia

    en.wikipedia.org/wiki/CuPy

    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] CuPy shares the same API set as NumPy and SciPy, allowing it to be a drop-in replacement to run NumPy/SciPy code on GPU.

  4. Simulation Open Framework Architecture - Wikipedia

    en.wikipedia.org/wiki/Simulation_Open_Framework...

    Simulation Open Framework Architecture (SOFA) [1] is an open source framework primarily targeted at real-time physical simulation, with an emphasis on medical simulation.. It is mostly intended for the research community to help develop newer algorithms, but can also be used as an efficient prototyping tool or as a physics engine.

  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

  6. Parallel Thread Execution - Wikipedia

    en.wikipedia.org/wiki/Parallel_Thread_Execution

    Writing kernels in PTX requires explicitly registering PTX modules via the CUDA Driver API, typically more cumbersome than using the CUDA Runtime API and Nvidia's CUDA compiler, nvcc. The GPU Ocelot project provided an API to register PTX modules alongside CUDA Runtime API kernel invocations, though the GPU Ocelot is no longer actively maintained.

  7. 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.

  8. rCUDA - Wikipedia

    en.wikipedia.org/wiki/RCUDA

    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.

  9. OptiX - Wikipedia

    en.wikipedia.org/wiki/OptiX

    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 ...