Search results
Results from the WOW.Com Content Network
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 ...
Download QR code ; Print/export ... 5th gen: 2.2 win 10+ and Linux RocM 5.0+ 2.2+ and 3.0 windows 8.1+ and ... The HD5000 series is the last series of AMD GPUs which ...
GPUOpen HIP: A thin abstraction layer on top of CUDA and ROCm intended for AMD and Nvidia GPUs. Has a conversion tool for importing CUDA C++ source. Supports CUDA 4.0 plus C++11 and float16. ZLUDA is a drop-in replacement for CUDA on AMD GPUs and formerly Intel GPUs with near-native performance. [33]
Wolfram Mathematica 10 [74] and later Wolfram Research: 2014 Proprietary: No Windows, macOS, Linux, Cloud computing: C++, Wolfram Language, CUDA: Wolfram Language: Yes No Yes No Yes Yes [75] Yes Yes Yes Yes [76] Yes Software Creator Initial release Software license [a] Open source Platform Written in Interface OpenMP support OpenCL support CUDA ...
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]
Windows XP: 02.1: 14.4: Driver updates and support stopped at AMD Catalyst 14.4 for video cards with support up to DirectX 11 on Hardware, and 10.2 for DirectX 9.0c cards. [citation needed] Windows Vista: 7.2: 13.12: Driver updates and support stopped at AMD Catalyst 13.12 for video cards with support up to DirectX 11. [citation needed] Windows ...
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]
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.