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  2. Free and open-source graphics device driver - Wikipedia

    en.wikipedia.org/wiki/Free_and_open-source...

    The Videocore GPU runs an RTOS which handles the processing; video acceleration is done with RTOS firmware coded for its proprietary GPU, and the firmware was not open-sourced on that date. [92] Since there was neither a toolchain targeting the proprietary GPU nor a documented instruction set , no advantage could be taken if the firmware source ...

  3. CUDA - Wikipedia

    en.wikipedia.org/wiki/CUDA

    CUDA is a software layer that gives direct access to the GPU's virtual instruction set and parallel computational elements for the execution of compute kernels. [6] In addition to drivers and runtime kernels, the CUDA platform includes compilers, libraries and developer tools to help programmers accelerate their applications.

  4. PyTorch - Wikipedia

    en.wikipedia.org/wiki/PyTorch

    PyTorch 2.0 was released on 15 March 2023, introducing TorchDynamo, a Python-level compiler that makes code run up to 2x faster, along with significant improvements in training and inference performance across major cloud platforms.

  5. DeepSpeed - Wikipedia

    en.wikipedia.org/wiki/DeepSpeed

    Features include mixed precision training, single-GPU, multi-GPU, and multi-node training as well as custom model parallelism. The DeepSpeed source code is licensed under MIT License and available on GitHub. [5] The team claimed to achieve up to a 6.2x throughput improvement, 2.8x faster convergence, and 4.6x less communication. [6]

  6. AMD Software - Wikipedia

    en.wikipedia.org/wiki/AMD_Software

    Radeon Software 17.7.1 is the final driver for Windows 8.1. Radeon Software 18.9.3 is the final driver for 32-bit Windows 7/10. AMD Software 22.6.1 is the final driver for Windows 7 (and Windows 8.1 unofficially); 22.6.1 is also the final driver for GCN 1, GCN 2 and GCN 3 based GPUs [43]

  7. TensorFlow - Wikipedia

    en.wikipedia.org/wiki/TensorFlow

    While the reference implementation runs on single devices, TensorFlow can run on multiple CPUs and GPUs (with optional CUDA and SYCL extensions for general-purpose computing on graphics processing units). [18] TensorFlow is available on 64-bit Linux, macOS, Windows, and mobile computing platforms including Android and iOS. [citation needed]

  8. WoW64 - Wikipedia

    en.wikipedia.org/wiki/WoW64

    In computing on Microsoft platforms, WoW64 (Windows 32-bit on Windows 64-bit) is a subsystem of the Windows operating system capable of running 32-bit applications on 64-bit Windows. [1] It is included in all 64-bit versions of Windows, except in Windows Server Server Core where it is an optional component, and Windows Nano Server where it is ...

  9. General-purpose computing on graphics processing units

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

    This has implications for correctness which are considered important to some scientific applications. While 64-bit floating point values (double precision float) are commonly available on CPUs, these are not universally supported on GPUs. Some GPU architectures sacrifice IEEE compliance, while others lack double-precision.