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TensorFlow is available on 64-bit Linux, macOS, Windows, and mobile computing platforms including Android and iOS. [ citation needed ] Its flexible architecture allows for easy deployment of computation across a variety of platforms (CPUs, GPUs, TPUs ), and from desktops to clusters of servers to mobile and edge devices .
Unlike OpenCL, CUDA-enabled GPUs are only available from Nvidia as it is proprietary. [28] [2] Attempts to implement CUDA on other GPUs include: Project Coriander: Converts CUDA C++11 source to OpenCL 1.2 C. A fork of CUDA-on-CL intended to run TensorFlow. [29] [30] [31] CU2CL: Convert CUDA 3.2 C++ to OpenCL C. [32]
Altimesh Hybridizer created by Altimesh compiles Common Intermediate Language to CUDA binaries. [15] [16] It supports generics and virtual functions. [17] Debugging and profiling is integrated with Visual Studio and Nsight. [18] It is available as a Visual Studio extension on Visual Studio Marketplace.
PyTorch defines a class called Tensor (torch.Tensor) to store and operate on homogeneous multidimensional rectangular arrays of numbers.PyTorch Tensors are similar to NumPy Arrays, but can also be operated on a CUDA-capable NVIDIA GPU.
PlaidML is a portable tensor compiler.Tensor compilers bridge the gap between the universal mathematical descriptions of deep learning operations, such as convolution, and the platform and chip-specific code needed to perform those operations with good performance.
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]
It is designed to follow the structure and workflow of NumPy as closely as possible and works with various existing frameworks such as TensorFlow and PyTorch. [5] [6] The primary functions of JAX are: [2] grad: automatic differentiation; jit: compilation; vmap: auto-vectorization; pmap: Single program, multiple data (SPMD) programming
Pro Windows Subsystem for Linux (WSL): Powerful Tools and Practices for Cross-Platform Development and Collaboration. Apress. ISBN 978-1484268728. Leeks, Stuart (2020). Windows Subsystem for Linux 2 (WSL 2) Tips, Tricks, and Techniques: Maximise productivity of your Windows 10 development machine with custom workflows and configurations. Packt ...