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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 [27] and Apple's Metal Framework. [28] PyTorch supports various sub-types of Tensors. [29]
ROCm [3] is an Advanced Micro Devices (AMD) software stack for graphics processing unit (GPU) programming. ROCm spans several domains: general-purpose computing on graphics processing units (GPGPU), high performance computing (HPC), heterogeneous computing.
AMD Software (formerly known as Radeon Software) is a device driver and utility software package for AMD's Radeon graphics cards and APUs. Its graphical user interface is built with Qt [ 6 ] and is compatible with 64-bit Windows and Linux distributions .
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] CuPy shares the same API set as NumPy and SciPy, allowing it to be a drop-in replacement to run NumPy/SciPy code on GPU.
Advanced Micro Devices (AMD) joins the newly-launched PyTorch foundation to create a sustainable ecosystem of open-source projects with PyTorch and drive the growing adoption of AI.
In computing, CUDA is a proprietary [1] parallel computing platform and application programming interface (API) that allows software to use certain types of graphics processing units (GPUs) for accelerated general-purpose processing, an approach called general-purpose computing on GPUs.
Torch is used by the Facebook AI Research Group, [8] IBM, [9] Yandex [10] and the Idiap Research Institute. [11] Torch has been extended for use on Android [12] [better source needed] and iOS. [13] [better source needed] It has been used to build hardware implementations for data flows like those found in neural networks. [14]
The Vega microarchitecture was AMD's high-end graphics cards line, [13] and is the successor to the R9 300 series enthusiast Fury products. Partial specifications of the architecture and Vega 10 GPU were announced with the Radeon Instinct MI25 in December 2016. [14] AMD later released the details of the Vega architecture.