Shulou(Shulou.com)11/24 Report--

Thanks to CTOnews.com netizen OC_Formula for the clue delivery! CTOnews.com October 31, TensorFlow is an end-to-end open source machine learning platform. It has a comprehensive and flexible ecosystem of tools, libraries, and community resources, and with TensorFlow, beginners and experts can easily create machine learning models for desktop, mobile, Web, and cloud environments.

With the release of Intel's own sharp show, Intel officially announced the launch of Intel Extension for TensorFlow, an open source solution that runs TensorFlow applications on Intel AI hardware.

According to reports, Intel Extension for TensorFlow is a high-performance deep learning extension that implements the TensorFlow PluggableDevice interface. Through seamless integration with the TensorFlow framework, it allows TensorFlow developers easy access to Intel XPU (GPU, CPU, etc.) devices. With Intel extensions, developers can train and infer TensorFlow models on Intel AI hardware with zero code changes.

Intel Extension for TensorFlow is built on top of oneAPI software components. Most performance critical diagrams and operators are highly optimized using Intel oneAPI Deep Neural Network (oneDNN), an open source cross-platform performance library for deep learning applications. Other operators are implemented using SYCL, an API core language for programming accelerators and multiprocessors.

▲ foreign media phoronix tested the plug-in and maintained a native Eigen math library that migrates Eigen to the SYCL language so that it can generate SYCL kernel programs to implement device operators. Intel Extension for TensorFlow also implements all TensorFlow GPU operators to ensure that Intel GPU has good performance and sufficient model coverage.

CTOnews.com learned that Intel Extension for TensorFlow can be used with the Flex series of data center GPU and Intel sharp series for Linux and Windows 11's Linux subsystem (WSL2).

Intel Extension for TensorFlow: click here to view

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