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  2. 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.

  3. CUDA - Wikipedia

    en.wikipedia.org/wiki/CUDA

    CUDA is designed to work with programming languages such as C, C++, Fortran and Python. This accessibility makes it easier for specialists in parallel programming to use GPU resources, in contrast to prior APIs like Direct3D and OpenGL , which require advanced skills in graphics programming. [ 6 ]

  4. OpenACC - Wikipedia

    en.wikipedia.org/wiki/OpenACC

    An experimental [17] open source compiler, accULL, is developed by the University of La Laguna (C language only). [ 18 ] Omni Compiler [ 19 ] [ 20 ] is an open source compiler developed at HPCS Laboratory. of University of Tsukuba and Programming Environment Research Team of RIKEN Center for Computational Science, Japan, supported OpenACC ...

  5. Parallel Thread Execution - Wikipedia

    en.wikipedia.org/wiki/Parallel_Thread_Execution

    Parallel Thread Execution (PTX or NVPTX [1]) is a low-level parallel thread execution virtual machine and instruction set architecture used in Nvidia's Compute Unified Device Architecture programming environment. The Nvidia CUDA Compiler (NVCC) translates code written in CUDA, a C++-like language, into PTX instructions (an assembly language ...

  6. oneAPI (compute acceleration) - Wikipedia

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

    The oneAPI specification extends existing developer programming models to enable multiple hardware architectures through a data-parallel language, a set of library APIs, and a low-level hardware interface to support cross-architecture programming. It builds upon industry standards and provides an open, cross-platform developer stack. [6] [7]

  7. 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.

  8. Dark chocolate may help lower type 2 diabetes risk

    www.aol.com/dark-chocolate-may-help-lower...

    “The findings emphasize the importance of food choices in managing metabolic health. While dark chocolate may offer some protective benefits against type 2 diabetes, it should not be viewed as a ...

  9. 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.

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