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  2. CuPy - Wikipedia

    en.wikipedia.org/wiki/CuPy

    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. 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 ...

  3. Parallel Thread Execution - Wikipedia

    en.wikipedia.org/wiki/Parallel_Thread_Execution

    Shared memory is declared in the PTX file via lines at the start of the form: .shared .align 8 .b8 pbatch_cache [ 15744 ]; // define 15,744 bytes, aligned to an 8-byte boundary 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 ...

  4. 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]

  5. Comparison of API simulation tools - Wikipedia

    en.wikipedia.org/wiki/Comparison_of_API...

    The tools listed here support emulating [1] or simulating APIs and software systems. They are also called [2] API mocking tools, service virtualization tools, over the wire test doubles and tools for stubbing and mocking HTTP(S) and other protocols. [1] They enable component testing in isolation. [3]

  6. oneAPI (compute acceleration) - Wikipedia

    en.wikipedia.org/wiki/OneAPI_(compute_acceleration)

    oneAPI is an open standard, adopted by Intel, [1] for a unified application programming interface (API) intended to be used across different computing accelerator (coprocessor) architectures, including GPUs, AI accelerators and field-programmable gate arrays. It is intended to eliminate the need for developers to maintain separate code bases ...

  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. 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.

  9. Kaggle - Wikipedia

    en.wikipedia.org/wiki/Kaggle

    Kaggle is a data science competition platform and online community for data scientists and machine learning practitioners under Google LLC.Kaggle enables users to find and publish datasets, explore and build models in a web-based data science environment, work with other data scientists and machine learning engineers, and enter competitions to solve data science challenges.

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