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  2. 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 ...

  3. AMD Software - Wikipedia

    en.wikipedia.org/wiki/AMD_Software

    ROCm 6.0 was released ... PyTorch and ONNX Runtime can be ... Radeon Software 18.9.3 is the final driver for 32-bit Windows 7/10. AMD Software 22.6.1 is the ...

  4. 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]

  5. Comparison of deep learning software - Wikipedia

    en.wikipedia.org/wiki/Comparison_of_deep...

    Format name Design goal Compatible with other formats Self-contained DNN Model Pre-processing and Post-processing Run-time configuration for tuning & calibration

  6. List of AMD graphics processing units - Wikipedia

    en.wikipedia.org/wiki/List_of_AMD_graphics...

    AMD support Year introduced Introduced with Rendering Computing / ROCm; Vulkan [17] OpenGL [18] Direct3D HSA OpenCL; Wonder: Fixed-pipeline [a] 1000 nm 800 nm — — — — — Ended 1986 Graphics Solutions Mach: 800 nm 600 nm 1991 Mach8 3D Rage: 500 nm 5.0 1996 3D Rage Rage Pro: 350 nm 1.1 6.0 1997 Rage Pro Rage 128: 250 nm 1.2 1998 Rage 128 ...

  7. PyTorch - Wikipedia

    en.wikipedia.org/wiki/PyTorch

    PyTorch Tensors are similar to NumPy Arrays, but can also be operated on a CUDA-capable NVIDIA GPU. PyTorch has also been developing support for other GPU platforms, for example, AMD's ROCm [26] and Apple's Metal Framework. [27] PyTorch supports various sub-types of Tensors. [28]

  8. bfloat16 floating-point format - Wikipedia

    en.wikipedia.org/wiki/Bfloat16_floating-point_format

    Many libraries support bfloat16, such as CUDA, [13] Intel oneAPI Math Kernel Library, AMD ROCm, [14] AMD Optimizing CPU Libraries, PyTorch, and TensorFlow. [10] [15] On these platforms, bfloat16 may also be used in mixed-precision arithmetic, where bfloat16 numbers may be operated on and expanded to wider data types.

  9. GPUOpen - Wikipedia

    en.wikipedia.org/wiki/GPUOpen

    Nicolas Thibieroz, AMD's Senior Manager of Worldwide Gaming Engineering, argues that "it can be difficult for developers to leverage their R&D investment on both consoles and PC because of the disparity between the two platforms" and that "proprietary libraries or tools chains with "black box" APIs prevent developers from accessing the code for maintenance, porting or optimizations purposes". [7]