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  2. Forward compatibility - Wikipedia

    en.wikipedia.org/wiki/Forward_compatibility

    Forward compatibility or upward compatibility is a design characteristic that allows a system to accept input intended for a later version of itself. The concept can be applied to entire systems, electrical interfaces , telecommunication signals , data communication protocols , file formats , and programming languages .

  3. CUDA - Wikipedia

    en.wikipedia.org/wiki/CUDA

    In computing, CUDA (Compute Unified Device Architecture) is a proprietary [2] parallel computing platform and application programming interface (API) that allows software to use certain types of graphics processing units (GPUs) for accelerated general-purpose processing, an approach called general-purpose computing on GPUs.

  4. 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.

  5. 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]

  6. Software incompatibility - Wikipedia

    en.wikipedia.org/wiki/Software_incompatibility

    Software compatibility is a characteristic of software components or systems which can operate satisfactorily together on the same computer, or on different computers linked by a computer network. It is possible that some software components or systems may be compatible in one environment and incompatible in another.

  7. 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 ...

  8. Hopper (microarchitecture) - Wikipedia

    en.wikipedia.org/wiki/Hopper_(microarchitecture)

    Hopper allows CUDA compute kernels to utilize automatic inline compression, including in individual memory allocation, which allows accessing memory at higher bandwidth. This feature does not increase the amount of memory available to the application, because the data (and thus its compressibility ) may be changed at any time.

  9. List of finite element software packages - Wikipedia

    en.wikipedia.org/wiki/List_of_finite_element...

    It is an Open Source FEA project. The solver uses a partially compatible ABAQUS file format. The pre/post-processor generates input data for many FEA and CFD applications: Guido Dhondt, Klaus Wittig: 2.20: 2022-08-01: GNU GPL: Free: Linux, Windows: DIANA FEA: General purpose finite element package utilised by civil, structural and geotechnical ...