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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. [ 7 ]

  4. 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 ...

  5. Nvidia Jetson - Wikipedia

    en.wikipedia.org/wiki/Nvidia_Jetson

    It is packaged with newer versions of Tegra System Profiler, TensorRT, and cuDNN from the last release. [ 21 ] RedHawk Linux is a high-performance RTOS available for the Jetson platform, along with associated NightStar real-time development tools, CUDA/GPU enhancements, and a framework for hardware-in-the-loop and man-in-the-loop simulations.

  6. CS50 - Wikipedia

    en.wikipedia.org/wiki/CS50

    CS32 (Computational Thinking and Problem Solving), taught by Michael D. Smith, [29] is an alternative to CS50 but does not have a free online version. [30] The next course in sequence after CS32 or CS50 is CS51: Abstraction and Design in Computation, instructed by Stuart M. Shieber with Brian Yu as co-instructor. [31]

  7. ROCm - Wikipedia

    en.wikipedia.org/wiki/ROCm

    Installation instructions are provided for Linux and Windows in the official AMD ROCm documentation. ROCm software is currently spread across several public GitHub repositories. Within the main public meta-repository , there is an XML manifest for each official release: using git-repo , a version control tool built on top of Git , is the ...

  8. SYCL - Wikipedia

    en.wikipedia.org/wiki/SYCL

    Unlike C++ AMP and CUDA, SYCL is a pure C++ eDSL without any C++ extension. This allows for a basic CPU implementation that relies on pure runtime without any specific compiler. [40] Both DPC++ [45] and AdaptiveCpp [46] compilers provide a backend to NVIDIA GPUs, similar to how CUDA does. This allows SYCL code to be compiled and run on NVIDIA ...

  9. oneAPI (compute acceleration) - Wikipedia

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

    oneAPI is an open standard, adopted by Intel, [1] for a unified application programming interface (API) intended to be used across different computing accelerator (coprocessor) architectures, including GPUs, AI accelerators and field-programmable gate arrays. It is intended to eliminate the need for developers to maintain separate code bases ...

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