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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]

  3. 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project provided an API to register PTX modules alongside CUDA Runtime API kernel invocations, though the GPU Ocelot is no longer actively maintained.

  4. SYCL - Wikipedia

    en.wikipedia.org/wiki/SYCL

    However, there is a less known non-single-source version of CUDA, which is called "CUDA Driver API," similar to OpenCL, and used, for example, by the CUDA Runtime API implementation itself. [ 38 ] SYCL extends the C++ AMP features, relieving the programmer from explicitly transferring data between the host and devices by using buffers and ...

  5. 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.

  6. 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

  7. 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.

  8. 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 .

  9. Thread block (CUDA programming) - Wikipedia

    en.wikipedia.org/wiki/Thread_block_(CUDA...

    CUDA is a parallel computing platform and programming model that higher level languages can use to exploit parallelism. In CUDA, the kernel is executed with the aid of threads. The thread is an abstract entity that represents the execution of the kernel. A kernel is a function that compiles to run on a special device. Multi threaded ...