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  2. 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]

  3. CUDA - Wikipedia

    en.wikipedia.org/wiki/CUDA

    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, [17] which supersedes the beta released February 14, 2008. [18] CUDA works with all Nvidia GPUs from the G8x series onwards, including GeForce, Quadro and the Tesla line. CUDA is compatible with most ...

  4. General-purpose computing on graphics processing units

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

    Before CUDA was published in 2007, GPGPU was "classical" and involved repurposing graphics primitives. A standard structure of such was: Load arrays into textures; Draw a quadrangle; Apply pixel shaders and textures to quadrangle; Read out pixel values in the quadrangle as array; More examples are available in part 4 of GPU Gems 2. [35]

  5. Graphics pipeline - Wikipedia

    en.wikipedia.org/wiki/Graphics_pipeline

    The rasterization step is the final step before the fragment shader pipeline that all primitives are rasterized with. In the rasterization step, discrete fragments are created from continuous primitives. In this stage of the graphics pipeline, the grid points are also called fragments, for the sake of greater distinctiveness.

  6. 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 ...

  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. Shadow mapping - Wikipedia

    en.wikipedia.org/wiki/Shadow_mapping

    Drawing the scene with shadows can be done in several different ways. If programmable shaders are available, the depth map test may be performed by a fragment shader which simply draws the object in shadow or lighted depending on the result, drawing the scene in a single pass (after an initial earlier pass to generate the shadow map).

  9. Compute kernel - Wikipedia

    en.wikipedia.org/wiki/Compute_kernel

    In computing, a compute kernel is a routine compiled for high throughput accelerators (such as graphics processing units (GPUs), digital signal processors (DSPs) or field-programmable gate arrays (FPGAs)), separate from but used by a main program (typically running on a central processing unit).