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  2. CUDA - Wikipedia

    en.wikipedia.org/wiki/CUDA

    CUDA 9.0–9.2 comes with these other components: CUTLASS 1.0 – custom linear algebra algorithms, NVIDIA Video Decoder was deprecated in CUDA 9.2; it is now available in NVIDIA Video Codec SDK; CUDA 10 comes with these other components: nvJPEG – Hybrid (CPU and GPU) JPEG processing; CUDA 11.0–11.8 comes with these other components: [20 ...

  3. OpenCV - Wikipedia

    en.wikipedia.org/wiki/OpenCV

    OpenCV runs on the desktop operating systems: Windows, Linux, macOS, FreeBSD, NetBSD and OpenBSD as well as mobile operating systems: Android, iOS, Maemo, [19] BlackBerry 10 and QNX. [20] The user can get official releases from SourceForge or take the latest sources from GitHub. [21] OpenCV uses CMake.

  4. 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.

  5. 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.

  6. Vulkan - Wikipedia

    en.wikipedia.org/wiki/Vulkan

    Vulkan targets high-performance real-time 3D-graphics applications, such as video games and interactive media, and highly parallelized computing.Vulkan is intended to offer higher performance and more efficient CPU and GPU usage compared to the older OpenGL and Direct3D 11 APIs.

  7. Tegra - Wikipedia

    en.wikipedia.org/wiki/Tegra

    It contains 7 billion transistors and 8 custom ARMv8 cores, a Volta GPU with 512 CUDA cores, an open sourced TPU (Tensor Processing Unit) called DLA (Deep Learning Accelerator). [132] [133] It is able to encode and decode 8K Ultra HD (7680×4320). Users can configure operating modes at 10 W, 15 W, and 30 W TDP as needed and the die size is 350 ...

  8. OpenMP - Wikipedia

    en.wikipedia.org/wiki/OpenMP

    OpenMP is an application programming interface (API) that supports multi-platform shared-memory multiprocessing programming in C, C++, and Fortran, [3] on many platforms, instruction-set architectures and operating systems, including Solaris, AIX, FreeBSD, HP-UX, Linux, macOS, Windows and OpenHarmony.

  9. OpenCL - Wikipedia

    en.wikipedia.org/wiki/OpenCL

    OpenCL (Open Computing Language) is a framework for writing programs that execute across heterogeneous platforms consisting of central processing units (CPUs), graphics processing units (GPUs), digital signal processors (DSPs), field-programmable gate arrays (FPGAs) and other processors or hardware accelerators.